Sensor plant and method for identifying stressors in crops based on characteristics of sensor plants

ABSTRACT

One variation of a method for identifying stressors in crops based on fluorescence of sensor plants includes: accessing a set of spectral images of a sensor plant sown in a crop, the sensor plant of a sensor plant type including a set of promoters and a set of reporters configured to signal a set of stressors present at the sensor plant, the set of promoters and set of reporters forming a set of promoter-reporter pairs; accessing a reporter model linking characteristics extracted from the set of spectral images of the sensor plant to the set of stressors based on signals generated by the set of promoter-reporter pairs in the sensor plant type; and identifying a first stressor, in the set of stressors, present at the sensor plant based on the reporter model and characteristics extracted from the set of spectral images.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a continuation application of U.S. patentapplication Ser. No. 16/72,1830, filed on 19 Dec. 2019, which claims thebenefit of U.S. Provisional Application No. 62/894,676, filed on 30 Aug.2019, U.S. Provisional Application No. 62/864,401, filed on 20 Jun.2019, and U.S. Provisional Application No. 62/782,130, filed on 19 Dec.2018, each of which are incorporated in its entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the field of agriculture and morespecifically to a new and useful sensor plant and method for identifyingstressors in crops based on characteristics of sensor plants in thefield of agriculture.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a first method;

FIG. 2 is a flowchart representation of the first method;

FIGS. 3A-3C are a flowchart representation of a second method;

FIGS. 4A and 4B are a flowchart representation of a third method;

FIGS. 5A and 5B are graphical representations of wavelength spectra;

FIG. 6 is a schematic representation of a remote sensor system; and

FIGS. 7A and 7B are graphical representations of solar spectra.

DESCRIPTION OF THE EMBODIMENTS

The following description of embodiments of the invention is notintended to limit the invention to these embodiments but rather toenable a person skilled in the art to make and use this invention.Variations, configurations, implementations, example implementations,and examples described herein are optional and are not exclusive to thevariations, configurations, implementations, example implementations,and examples they describe. The invention described herein can includeany and all permutations of these variations, configurations,implementations, example implementations, and examples.

1. Sensor Plant

As shown in FIG. 1 , a sensor plant includes a first promoter-reporterpair including: a first promoter that activates in the presence of afirst stressor at the sensor plant; a first reporter coupled to thefirst promoter and configured to exhibit a first signal in theelectromagnetic spectrum in response to activation of the first promoterby the first stressor. The sensor plant includes a secondpromoter-reporter pair including: a second promoter that activates inthe presence of a second stressor at the sensor plant; a second reportercoupled to the second promoter and configured to exhibit a second signalin the electromagnetic spectrum in response to activation of the firstpromoter by the second stressor, the second signal different from thefirst signal. The sensor plant further includes a third promoter thatactivates in the presence of a third stressor at the sensor plant; andthe first reporter and the second reporter are coupled to the thirdpromoter and are configured to exhibit a third signal in theelectromagnetic spectrum in response to activation of the third promoterby the third stressor, the third signal different from the first signaland the second signal.

One variation of the sensor plant includes a first promoter-reporterpair including: a first promoter configured to activate in the presenceof a first stressor within a first magnitude range at the sensor plant;and a first reporter coupled to the first promoter and configured toexhibit a first signal in the electromagnetic spectrum in response toactivation of the first promoter by the first stressor. In thisvariation, the sensor plant also includes a second promoter-reporterpair including: a second promoter configured to activate in the presenceof the first stressor within a second magnitude greater than the firstmagnitude range at the sensor plant; and a second reporter coupled tothe second promoter and configured to exhibit a second signal in theelectromagnetic spectrum in response to activation of the secondpromoter by the second stressor.

Another variation of the sensor plant includes: a first promoter thatactivates at a first time over a first duration in response to a firststressor presence in the sensor plant; a second promoter that activatesat a second time for a second duration in response to the first stressorpresence in the sensor plant, the second time succeeding the first andpreceding the termination of the first duration; and a reporter coupledto the first and second promoter that, in response to activation of thefirst promoter, exhibits a first signal over the first duration fordetection of the first stressor; and, in response to activation of thesecond promoter, exhibits a second signal over the second duration fordetection of the first stressor.

1.1 Method

As shown in FIGS. 1 and 2 , a first method S100 for identifyingstressors in crops based on characteristics of sensor plants includes:accessing an image of a sensor plant sown in a crop in Block S110, thesensor plant of a sensor plant type including a set of promoters and aset of reporters configured to signal a set of stressors present at thesensor plant, the set of promoters and set of reporters forming a set ofpromoter-reporter pairs; accessing a reporter model linking featuresextracted from images of the sensor plant type to the set of stressorsbased on signals generated by the set of promoter-reporter pairs in thesensor plant type in Block S120; identifying a first stressor, in theset of stressors, present at the sensor plant based on the reportermodel and features extracted from the image in Block S130; isolating afirst action, in a set of actions defined for the sensor plant type,linked to the first stressor in Block S140; and, in response toidentifying the first stressor, prompting a farmer to perform the firstaction at the crop to mitigate the first stressor in Block S150.

1.2 Applications

Generally, a sensor plant includes a promoter-reporter pair configuredto detect stressors present in the sensor plant and to produce adetectable signal (e.g., in the electromagnetic spectrum) to indicatepresence of these stressors in the sensor plant or in a region of a cropwhere the sensor plant is located more generally. More specifically, asensor plant can be genetically modified to include: a promoter genesequence (hereinafter a “promoter”) configured to activate in thepresence of (e.g., “linked to”) a particular stressor; and a reportergene sequence (hereinafter a “reporter”) paired to the promoter andconfigured to exhibit (or “express”) a signal when the promoter isactive.

A computer system (e.g., a remote server, a local device, a computernetwork) can then execute Blocks of the method to detect this signal inan image of this sensor plant and to interpret this signal as presence(and/or duration, magnitude) of this particular stressor. In particular,the computer system can: access an image of the sensor plant (e.g., thesensor plant specifically, a cluster of plants including the sensorplant, a whole crop field); detect the sensor plant in a region of theimage; extract intensity of a particular signal (e.g., anelectromagnetic signal in the visible light or infraredspectrum)—generated by a promoter-reporter pair for this sensor planttype in the presence of the particular stressor—from this region of theimage depicting the sensor plant; and then predict presence of theparticular stressor at the sensor plant if this intensity of theparticular signal exceeds a threshold intensity. The computer system canadditionally or alternatively: predict a duration of time that theparticular plant pressure was present at the sensor plant; predict amagnitude of the particular plant pressure at the sensor plant based onthis intensity of the particular signal; and/or isolate a particularcourse of action to address presence of the particular stressor at thesensor plant, such as based on a link between the particular signal andthe particular course of action defined by the reporter model.Accordingly, the computer system can alert a farmer or other entityaffiliated with the sensor plant or crop of presence, duration, and/ormagnitude of the particular stressor in the sensor plant and/or promptthe farmer to perform the particular course of action at the sensorplant (and surrounding plants, field, or crop) to eradicate or mitigatethe particular stressor.

In one implementation, an imaging system (e.g., a multispectral orhyperspectral imaging system) can capture digital images (e.g., spectralimages) of a plant canopy (e.g., sensor plants and surrounding plants).For example, the imaging system can include: an optomechanical foreoptic that enables measurement of fluorescent and non-fluorescenttargets; and a digital spectrometer or digital camera that recordsimages through the optomechanical fore optic. The computer system canthus access images recorded by the imaging system and process theseimages according to the method S100 to detect reporter signals andinterpret pressures present in these plants.

In one variation, promoter-reporter pairs are incorporated into GMOplant genes within a GMO stack already present in GMO seeds, which maythen be planted to produce an entire crop of sensor plants (e.g.,non-sterile GMO sensor plants). These sensor plant seeds can beconfigured to generate several distinct signals that represent an arrayof stresses, as described below. For example, sensor plants includingdifferent promoter-reporter pairs can be distributed evenly throughout acrop. Alternatively, sensor plants can be planted in clusters within thefield wherein all plants within each cluster contain the samepromoter-reporter pair(s) configured to produce a particular signalresponsive to a particular biotic or abiotic stressor (or for aparticular set or class of biotic and/or abiotic stressors). Forexample, sensing plant seeds containing the same promoter-reporter pairscan be planted along the full length of one crop row in a field with(non-sterile) sensing plant seeds in the two adjacent crops rowscontaining different promoter-reporter pairs configured to producedifferent (or the same) signals responsive to different biotic orabiotic stressors. (In this example, this pattern of rows containingseeds with different promoter-reporter pairs can be repeated along thefull length of the field.)

By thus clustering sensor plants in one-dimensional or two-dimensionalgroups of sensor plants including the same promoter-reporter pairs andtherefore configured to produce signals responsive to the samestressors, the crop as a whole can produce high-amplitudesignals—characterized by high signal-to-noise ratios—for multipledifferent biotic and/or abiotic stressors in discrete rows or regions ofthe field. The computer system can thus execute Blocks of the methodS100 to interpolate or extrapolate stressors—indicated by these rows orclusters of sensor plants configured to produce signals responsive tothese stressors—across the entire field in order to predict stressorpressures across the entire crop. Therefore, in this variation, becauseeach plant in the field exhibits sensing capabilities, the computersystem can monitor the entire crop directly via a fixed or mobileimaging system and can generate a pressure map of biotic and/or abioticstressors for the crop as a whole based on signals produced by thesesensor plants during over time (e.g., once per day) and detected inimages of the crop. By repeating this process to develop new pressuremaps for the field over time, the computer system can monitor stressorsacross the field over time and serve data and/or recommendations forproactive mitigation of these stressors to a farmer, agronomist, fieldoperator, automated system, inputs supplier, or other entity affiliatedwith the field. The computer system can also implement this process toupdate the pressure map for the field following a stressor treatment atthe field, thereby enabling a field operator to directly assess efficacyof this stressor treatment and to make more informed treatment decisionsfor the field in the future.

1.3 Promoter-Reporter Pair

A sensor plant can be genetically modified to include promoter andreporter pairs that indicate presence of stressors in the sensor plant.A promoter includes genetic regulatory elements that drive expression ofmRNA at a specific time and place that is subsequently translated into afunctional protein. Promoter activity is representative of nativebiological processes that occur when a particular stressor is present inthe sensor plant. To detect presence of these stressors, a reporter thatexpresses a certain signal can be coupled to the promoter of choice.More specifically, the reporter can initiate a metabolic change in thesensor plant such that a detectable signal is produced (e.g., apigmentation change in the sensor plant). Therefore, when the sensorplant's cells express the promoter associated with a particularstressor, the reporter tagged to the promoter is also expressed andproduces a detectable signal. For example, the sensing plant can begenetically modified to fluoresce (i.e., absorb photons at one frequencyand emit photons at a different frequency) in the presence of (andproportional to) a disease or stressor pressure. In this example, thesensing plant can be modified to fluoresce in the presence of one ormore disease or stressor pressures, such as: fungi, bacteria, nematodes,parasites, viruses, insects, heat, water stress, nutrient stress,phytoplasmal disease, etc.

In one example, the sensor plant is genetically modified to include apromoter with activity representative of a native biological processthat occurs in the presence of an insect pressure in the sensor plant.In this example, the promoter is paired to a red fluorescence proteinreporter such that the resulting promoter-reporter pair is configured toexhibit red fluorescence in presence of the insect pressure in thesensor plant.

In one variation, the sensor plant can be genetically modified toinclude a particular promoter-reporter pair. For example, at a firsttime, the sensor plant can be genetically modified via geneticengineering techniques to associate bioluminescence of the sensor plant(initiated by a reporter) to a promoter linked to a particular metabolicprocess indicative of water stress in the sensor plant. At a later time,in response to a water level in the sensor plant cells falling below aminimum water concentration, the sensor plant can: initiate theparticular metabolic process, and therefore express the promoter;express the reporter and initiate a metabolic process linked to plantbioluminescence; and signal—via bioluminescence of the sensor plant—awater concentration below the minimum water concentration.

Therefore, the sensor plant can include a promoter-reporter pairconfigured to signal presence of particular biotic and/or abioticpressures experienced by the sensor plant, such as pest, disease, water,heat, soil health, and/or nutrient stresses or deficiencies. Forexample, the sensor plant can be genetically modified to include apromoter with activity linked to presence of one stressor at the plant,such as a fungal, pest, heat, water, disease, or nutrient stress. Thesensor plant can also be genetically modified to include a reporterpaired with the promoter and configured to produce a detectablesignal—such as an electromagnetic signal in the visible light orinfrared spectrum—when the corresponding promoter is activated. Forexample, the reporter in the sensor plant can be configured to fluoresce(i.e., produce a signal in the visible spectrum) when the correspondingpromoter is active in the sensor plant. More specifically, apromoter-reporter pair can be incorporated into the sensor plant viamolecular binding and metabolic engineering techniques that associateexpression of a promoter responsive to a particular biological stresswith a reporter that produces a measurable signal when the promoterexpresses. The promoter-reporter pair can be configured to produce ameasurable signal by pairing the reporter with the promoter, such thatwhen the promoter expresses the reporter also expresses. Therefore, viaexpression of the reporter, the promoter-reporter pair can produce ameasurable signal of a particular biological stress or trait in thesensor plant.

1.3.1 Multiple Promoter-Reporter Pairs

In one variation, the sensor plant can be genetically modified toinclude multiple promoter-reporter pairs, each promoter-reporter pairindicative of a particular biological process occurring in the sensorplant cells in response to a particular stressor. For example, thesensor plant can include: a first promoter-reporter pair including afirst promoter representative of a first biological process linked topresence of a water stressor tagged to a red fluorescence proteinreporter; and a second promoter-reporter pair including a secondpromoter representative of a second biological process linked topresence of a fungi stressor tagged to a yellow fluorescence proteinreporter. Then, in response to presence of a fungi stressor in thesensor plant, the sensor plant can: initiate the second biologicalprocess, and therefore express the second promoter; express the yellowfluorescence protein reporter; and signal a fungi stressor magnitudeabove a threshold fungi stressor magnitude. Therefore, the sensor plantcan signal presence of multiple stressors via genetic modification ofthe sensor plant cells to include a set of promoter-reporter pairs.

In this variation, the computer system can distinguish between differentsignals from the sensor plant to determine which stressor is present inthe sensor plant. For example, the computer system can: access an imageof the sensor plant; access a reporter model linking characteristics ofthe image of the sensor plant to a particular stressor (e.g., yellowfluorescence signals a fungal pressure); identify a presence of theparticular stressor in the sensor plant based on the reporter model; andalert a farmer of the particular stressor in the sensor plant.

In another example, the sensor plant is genetically modified to includea set of promoters, wherein each promoter is representative of a uniquebiological process that occurs in response to a presence of a particularstressor in the sensor plant. In this example, the sensor plant isgenetically modified to include a set of promoters including: a firstpromoter configured to activate in the presence of an insect pressure; asecond promoter configured to activate in the presence of a fungalpressure; and a third promoter configured to activate in the presence ofa water-related pressure (e.g., too much and/or too little water). Eachpromoter in this set of promoters can be paired with a uniquereporter—in a set of reporters—in the sensor plant to form threepromoter-reporter pairs in the sensor plant. In particular: firstpromoter can be paired with a first reporter configured to express a redfluorescence protein; the second promoter can be paired with a secondreporter configured to express a yellow fluorescence protein; and thethird promoter can be paired with a third reporter configured to expressa green fluorescence protein. Then, the computer system can: access animage of the sensor plant, the image collected by a digitalspectrometer; access a reporter model linking expression of fluorescentproteins (e.g., red, yellow, green) as visible in the image of thesensor plant to plant stressors (e.g., red fluorescence signals aninsect pressure); in response to characteristics of the image of thesensor plant displaying yellow fluorescence, identify a fungal pressureat the sensor plant; and prompt a farmer of the fungal pressure in thesensor plant. Additionally, the computer system can link the fungalpressure to a particular action in a set of possible actions, and prompta farmer of the crop to apply fungicide to an infected area to mitigatethe fungal pressure.

1.3.2 Combinatorial Promoter-Reporter Pairs

In one variation, the sensor plant can be genetically modified toinclude a multiplexed gene sensing network representative of a set ofcombinatorial promoter-reporter pairs. The multiplexed gene sensingnetwork includes multiple promoters tied to one or more reporters. Thesensor plant can therefore include a set of promoters, each promoter inthe set of promoters paired to a reporter in a set of reporters or acombination of these reporters. For example, the sensor plant can begenetically modified to include: a first promoter paired to a redfluorescing reporter, the first promoter linked to a first biologicalprocess associated with a water stressor; a second promoter paired to ayellow fluorescing reporter, the second promoter linked to a secondbiological process associated with a fungal stressor; and a thirdpromoter paired to both the red fluorescing reporter and the yellowfluorescing reporter, the third promoter linked to a third biologicalprocess associated with a heat stressor. In response to the plant cellexceeding a threshold temperature, the sensor plant can: initiate thethird biological process, and therefore express the third promoter;express the red fluorescing reporter and the yellow fluorescingreporter; and signal presence of a heat stressor in the plant (e.g.,sensor plant temperature above a threshold temperature).

Therefore, the sensor plant can be genetically modified to include thismultiplexed gene sensing network to leverage a set of reporters todetect expression of a set of promoters linked to particular biologicalprocesses that occur in the plant. Thus, the sensor plant can leverage asmall number of reporters (e.g., fluorescing compounds) to monitor anddetect a greater number of promoters and/or biological processes andtherefore simplify the detection process by reducing the number ofreporters required, as fluorescent compounds exhibit broad spectralfeatures and may be difficult to simultaneously measure and distinguishbetween a large number of these fluorescent compounds.

1.4 Linked Promoter-Reporter Pairs

In one variation, the sensor plant includes a set of promoter-reporterpairs, each: configured to express a unique signal in the presence of aunique primary pressure; and configured to modify expression of itsunique signal in the presence of a secondary pressure.

In one example, the sensor plant can be genetically modified to include:a first promoter-reporter pair that expresses in a presence of a waterstressor; and a second promoter-reporter pair that expresses in apresence of a fungal stressor. Thus, in response to presence of thefungal stressor, the sensor plant can: increase expression of the secondpromoter-reporter pair to signal presence of the fungal stressor.However, the sensor plant may deactivate the first promoter-reporterpair in the course a natural response to this fungal stressor.

Therefore, in this example, the computer system can: access a sequenceof images of this sensor plant captured over a period of time; detectpresence of the fungal stressor at the sensor plant based on increasedintensity of a second signal associated with expression of the secondpromoter-reporter pair over this sequence of images; and confirmpresence of the fungal stressor based on decreased intensity of a firstsignal associated with expression of the first promoter-reporter pairover this sequence of images. If, however, the computer system detectsno change in magnitude of expression of the first promoter-reporter pairconcurrently with an increase in magnitude of expression of the secondpromoter-reporter pair, then the computer system can interpret adifferent stressor on the sensor plant. For example, if the secondreporter in the sensor plant is also linked to a third promoter for athird stressor (e.g., nutrient deficiency) that does not affectexpression of the first reporter-promoter pair, the computer system caninterpret presence of the third stressor at the sensor plant in responseto no detected change in magnitude of expression of the firstpromoter-reporter pair concurrently with an increase in magnitude ofexpression of the second promoter-reporter pair.

Therefore, the sensor plant can be configured to includepromoter-reporter pairs that signal presence of particular stressors inthe sensor plant and additionally alter expression of this signal in thepresence of a different stressor not associated with a particularpromoter-reporter pair. Thus, the computer system can: access images ofthe sensor plant; identify a particular stressor presence in the sensorplant based on characteristics of the images; and confirm the particularstressor presence in the sensor plant based on signals produced by otherpromoter-reporter pairs in the sensor plant or in nearby sensor plantsmatching predicted promoter-reporter pair expression in the presence ofthe particular stressor.

1.5 Linking Reporters to Courses of Action

In another variation, the sensor plant can include: a first promoterthat expresses in presence of a water stressor paired to a redfluorescence protein reporter to generate a first promoter-reporterpair; and a second promoter that expresses in presence of a heatstressor paired to a red fluorescence protein reporter to generate asecond promoter-reporter pair. Then, in response to a waterconcentration of the sensor plant falling below a minimum thresholdwater concentration (e.g., due to a hot dry day), the sensor plant cangenerate a red fluorescent signal for detection of the water stressor.Additionally and or/alternatively, in response to a temperature of thesensor plant exceeding a maximum threshold temperature, the sensor plantcan generate the red fluorescent signal for detection of the heatstressor. The computer system can: detect a stressor via images of thesensor plant; access a reporter model linking features of the images tostressors; identify the stressor as either a water stressor or a heatstressor; and prompt a farmer to irrigate the sensor plant and thesurrounding plants or crop. Therefore, the computer system can leverageunderstanding that multiple stressors may be mitigated or treated withthe same course of action to pair promoters representative of differentbiological processes or stressors to the same reporter or signal.

Therefore, the sensor plant can include one reporter linked to multiplepromoters configured to activate in the presence of different stressorsthat may be addressed and ameliorated with the same course of action.Furthermore, the computer system can: detect one signal expressed by thereporter in the presence of any pressure that activates a promoterlinked to the reporter; and output a recommendation for a course ofaction linked to this reporter and that, accordingly, may address any ofthe possible stressors present at the sensor plant.

1.6 Reporter Signaling Duration

In one variation, the sensor plant can be genetically modified toinclude multiple promoters linked to a particular biological process (orsimilar biological processes) and paired with a single reporter toincrease a duration over which the reporter is expressed. For example, asensor plant can be genetically modified to include a set of promoterspaired to one reporter, each promoter in the set of three promoterslinked to a biological process that occurs in the plant cells inresponse to presence of a water stressor. Each of these promoters can beselected and/or configured to express at different times while thebiological process is active.

For example, in response to a sensor plant water concentration fallingbelow a minimum water concentration, the sensor plant can: at a firsttime, initiate a particular biological process linked to plant celldehydration; express a first promoter in the set of promoters; andexpress the reporter for a first duration, signaling low waterconcentration in the sensor plant. Then, at a second time immediatelypreceding a termination of the first duration, the sensor plant can:continue activation of the particular biological process; express asecond promoter in the set of promoters; and express the reporter for asecond duration. Therefore, by pairing multiple promoters linked to asingle biological process with a single reporter, the sensor plant canincrease a total duration over which a reporter is expressed, thusincreasing a window of detection during which the sensor plant cansignal presence of a stressor in the sensor plant.

In a similar example, the sensor plant is genetically modified toinclude a set of promoters, wherein each promoter exhibits promoteractivity representative of the same native biological process thatoccurs in the presence of an insect pressure but is configured toactivate within a different time interval of the native biologicalprocess. In this example, a first promoter in the sensor plant can beconfigured to exhibit this promoter activity for the first day of aninsect pressure above a constitutive insect pressure; and a secondpromoter in the sensor plant can be configured to exhibit this promoteractivity for the second and third days of an insect pressure above theconstitutive insect pressure; etc. Furthermore, this set of promoterscan be paired to the red fluorescence protein reporter described above.Therefore, in the presence of an insect pressure over a period of time,the set of promoters can activate (approximately) consecutivelythroughout this time period, and the red fluorescence protein reportercan continue to express—in the form of a measurable signal—during thistime period as these promoters (approximately) consecutively activateand deactivate. Therefore, the sensor plant can exhibit red fluorescenceresponsive to this insect pressure over an extended duration of time,thereby increasing a window of time that this signal is measurable inthe sensor plant and thus extending a window of time in which a farmer,agronomist, or other entity may capture an image of the sensor plantthat the computer system can then interpret into presence of this insectpressure. In particular, the computer system can then: access an imageof this sensor plant; detect this signal—produced via expression of thisreporter responsive to activation of one of these promoters—in thisimage of the sensor plant; identify presence of the insect pressure inthe plant based on intensity of the signal thus detected in this image;and alert the farmer or agronomist of the insect pressure accordingly.The computer system can additionally or alternatively serve a prompt tothe farmer or agronomist to execute a particular course of action tomitigate this insect pressure, such as if the intensity of the signalthus detected in this image exceeds a threshold intensity.

1.7 Stressor Magnitude

In one variation, the sensor plant can generate signals of differentmagnitudes based on the magnitude of corresponding stressor pressures.For example, a sensor plant can be genetically modified to include apromoter-reporter pair configured to express a red fluorescent proteinin response to a fungal pressure presence in the sensor plant. Inresponse to the fungal pressure exceeding a minimum fungal pressurethreshold, the sensor plant can express the fluorescence protein togenerate a fluorescent signal above a threshold intensity. In responseto a fungal pressure exceeding a minimum fungal pressure threshold andfalling below an intermediate fungal pressure threshold, the sensorplant can express the fluorescence protein to generate a low levelsignal. Alternatively, in response to the fungal pressure exceeding theintermediate fungal pressure threshold, the sensor plant can express thefluorescence protein to generate a high level signal.

The computer system can distinguish different magnitudes of stressorpressures based on the signal generated by the sensor plant andtherefore prompt a particular course of action based on the magnitude ofstressor pressure in the sensor plant. In one variation, the computersystem can determine whether a sensor plant signal associated with aparticular stressor exceeds a signal threshold and then prompt a farmerto perform a particular course of action associated with the stressor ata particular magnitude. For example, the computer system can: detectexpression of a particular promoter-reporter pair via images of a sensorplant genetically modified to include the particular promoter-reporterpair; in response to expression of the particular promoter-reporterpair, measure a wavelength of fluorescence of the sensor plantcorresponding to a particular magnitude; and in response to theparticular magnitude falling above a threshold magnitude, prompt afarmer to perform a course of action (e.g., “apply fungicide”) in orderto mitigate or treat a stressor pressure (e.g., a fungal pressure).

In one variation, the sensor plant can generate signals of differentmagnitudes based on the magnitude of corresponding stressor pressures.For example, a sensor plant can be genetically modified to include apromoter-reporter pair configured to express a fluorescent protein inresponse to a fungal pressure presence in the sensor plant. In responseto a fungal pressure exceeding a minimum fungal pressure threshold andfalling below an intermediate fungal pressure threshold, the sensorplant can express the fluorescence protein to generate a low levelsignal at a first wavelength. Alternatively, in response to the fungalpressure exceeding the intermediate fungal pressure threshold andfalling below a maximum fungal pressure threshold, the sensor plant canexpress the fluorescence protein to generate an intermediate levelsignal at a second wavelength. Alternatively, in response to the fungalpressure exceeding the maximum fungal pressure threshold, the sensorplant can express the fluorescence protein to generate a high levelsignal at a third wavelength.

The computer system can distinguish different magnitudes of stressorpressures based on the signal generated by the sensor plant andtherefore prompt a particular course of action based on the magnitude ofstressor pressure in the sensor plant. For example, the computer systemcan: at a first time, measure a first wavelength of a sensor plant viaimages of the sensor plant; access a reporter model linking wavelengthsof sensor plants to magnitudes of stressor pressures; and calculate afirst magnitude of a stressor pressure at the first wavelength. Then, ata second time, the computer system can measure a second wavelength ofthe sensor plant and access the reporter model to calculate a secondmagnitude of the stressor pressure at the second wavelength.

In one variation, the computer system can prompt a particular course ofaction in response to the detection of a pressure magnitude above orbelow a threshold pressure magnitude. For example, the computer systemcan: at a first time, measure a first wavelength of a sensor plant viaimages of the sensor plant; access a reporter model linking wavelengthsof sensor plants to magnitudes of stressor pressures; and calculate afirst magnitude of a stressor pressure at the first wavelength. Then, inresponse to the first magnitude falling above a stressor pressuremagnitude, the computer system can inform a farmer of the stressorpressure and the corresponding magnitude, and prompt the farmer toperform a particular course of action (e.g., “irrigate the crop”).

1.8 Constitutive Reporter

In one variation, a sensor plant can be genetically modified to includea constitutive promoter-reporter pair to account for external factors(e.g., temperatures, pH levels) affecting promoter and reporterexpression. For example, an increase in plant temperature may reduce themagnitude of a fluorescence signal generated by sensor plants. Toaccount for this decrease in magnitude of the signal, a sensor plant canbe genetically modified to generate a constitutive sensor plant that cangenerate a signal unresponsive to changes in stressor but responsive toexternal factors. In one implementation, the sensor plant can begenetically modified to include: a constitutive promoter representativeof a native biological process that occurs in the sensor plantcontinuously, regardless of any stressor; and a constitutive reporterpaired to the promoter to generate a constitutive promoter-reporterpair. The sensor plant can express the constitutive promoter andtherefore the constitutive reporter both in the absence and presence ofstressors. The computer system can then measure a magnitude of a signalproduced by the sensor plant and record the magnitude as a constitutivemagnitude for this particular constitutive reporter.

For example, a sensor plant can be genetically modified to include: aconstitutive promoter representative of a native biological process thatoccurs in plants at all times; and a constitutive reporter that, whenexpressed, generates a red fluorescent signal, the constitutive reporterpaired to the constitutive promoter to form a constitutivepromoter-reporter pair. Additionally, a second sensor plant can begenetically modified to include: a promoter representative of abiological process that occurs in plants in the presence of a fungalpressure; and a reporter that, when expressed, generates the redfluorescent signal, the reporter paired to the promoter to form apromoter-reporter pair. The constitutive sensor plant can generate acontinuous red fluorescent signal that may alter in magnitude inresponse to various external factors or environmental conditions, butnot in response to a fungal pressure. When a fungal pressure is present,the second sensor plant can express the promoter-reporter pair andgenerate a signal with a first magnitude. The computer system can then:access images of both the second sensor plant and the constitutivesensor plant; measure wavelengths of both the first signal and theconstitutive signal; calculate a difference between the first signal andthe constitutive signal to estimate a relative magnitude of the firstsignal for the second sensor plant. Then, the computer system candetermine a particular course of action based on the relative magnitudeof the fungal pressure and prompt a farmer to perform this course ofaction. Therefore, the computer system can account for external factors(e.g., not related to the particular stressor associated with thepromoter-reporter pair) that cause changes in the reporter signal whenidentifying magnitudes of stressor pressures and determining theappropriate course of action.

In one variation, sensor plants can include a constitutivepromoter-reporter pair representative of a biological process thatoccurs in plants naturally in order to identify weeds and/or otherinvasive plant species in a crop. For example, a sensor plant caninclude a constitutive promoter-reporter pair that produces aconstitutive signal (e.g., an optical signal) at all times. The computersystem can detect this constitutive signal in an image of the crop andidentify the sensor plant and other plants naturally producing thissignal as crop plants accordingly. However, in response to failure todetect the constitutive signal and/or in response to detecting theconstitutive signal at an intensity less than a threshold signalintensity in an image of the crop, the computer system identify aweed(s) in the crop and alert a farmer of a weed presence in the cropaccordingly.

1.9 Sensor Plant Clusters

Sensor plants can be planted in crops of plants (e.g., crops of corn,crops of soybeans, etc.) to signal stressor pressures present in thecrop. In one variation, multiple sensor plants can be planted in acluster in designated sensor plant regions in the field, such as inspecific crop rows (e.g., every 50^(th) crop row) or in target segmentsof crop rows (e.g., three-row-wide, three-meter-long clusters with aminimum of 20 crop rows or 20 meters between adjacent clusters of sensorplants). By planting multiple sensor plants in clusters within a crop, acluster of sensor plants can produce a cumulative signal characterizedby a greater signal-to-noise ratio than a lone sensing plant.

In one variation, neighboring sensor plants can be genetically modifiedto include the same promoter-reporter pairs to increase magnitude of acumulative signal of the sensor plants. For example, a first sensorplant can be genetically modified to include a promoter-reporter pairconfigured to signal presence of an insect pressure within a crop. Thefirst sensor plant can be planted within a row of sensor plants—eachgenetically modified to include the same promoter-reporter pair—within acrop. In response to a migration of an insect pressure across the crop,the row of sensor plants—including the first sensor plant—can produce acumulative signal to indicate presence of the insect pressure.Therefore, by planting sensor plants in a cluster (e.g., row), thiscluster of sensor plants may also yield greater spatial informationregarding direction and scope of a stressor pressure moving across thecrop (e.g., an insect pressure migrating across the crop) than a lonesensor plant.

In one variation, a sensor plant can be genetically modified to includea different promoter-reporter pair than a neighboring sensor plant in acluster of sensor plants. For example, a cluster of sensor plants caninclude: a first sensor plant genetically modified to include a firstpromoter-reporter pair, the first promoter-reporter pair configured tosignal presence of an insect pressure in the first sensor plant; and asecond sensor plant genetically modified to include a secondpromoter-reporter pair, the second promoter-reporter pair configured tosignal presence of a fungi pressure in the second sensor plant. Inresponse to detecting an insect pressure, the first sensor plant cansignal presence of the insect pressure by expressing the firstpromoter-reporter pair to generate a detectable signal (e.g.,fluorescent light). Additionally or alternatively, in response todetecting a fungi pressure, the second sensor plant can signal presenceof the fungi pressure by expressing the promoter and reporters togenerate a detectable signal (e.g., fluorescent light). The computersystem can then: detect these signals via previously recorded or nearreal-time images of these sensor plants; access a reporter model linkingsensor plant signals to stressor pressures to identify the stressorpressure signaled by each sensor plant; and, in response to identifyingthe stressor pressure, identify a particular course of action based onthe stressor pressure; and prompt a farmer or crop manager to performthe particular course of action in order to mitigate the stressorpressure. Therefore, by planting clusters of sensor plants includingdifferent promoter-reporter pairs, the computer system can: detectsignals (e.g., presence) of multiple pressures; simplify identificationof stressor pressures (e.g., if each sensor plant includes onepromoter-reporter pair); and simplify image collection of the sensorplants and therefore detection of these stressor pressures by groupingsensor plants together in specific regions of a crop.

1.10 Sensor Plants in Cover Crops

In one implementation, sensor plants can be genetically modified toinclude: GMO plant genes within a GMO stack already present in GMOseeds; and promoter-reporter pairs configured to signal the presence ofstressors within the GMO crop. These sensor plants may then be plantedto produce an entire crop of sensor plants. In one variation, sensorplants can be planted as a cover crop (e.g., grasses, rye, wheat) thatis planted between regular crop rotations. Sensor plants can begenetically modified to include promoter-reporter pairs configured tomonitor soil health by sensing changes in soil health indicators suchas: salinity, pH, nutrient density, nematodes, organic matter, etc. Thesensor plants may then be planted between regular crop rotations (e.g.,during winter) to produce a cover crop configured to signal soil health.For example, sensor plants in a cover crop can be genetically modifiedto include promoter-reporter pairs configured to signal a pH level belowa minimum pH level and/or above a maximum pH level. In response todetecting a low pH level below a minimum pH level, sensor plants cansignal the low pH level by expressing the promoter and reporters togenerate a detectable signal (e.g., fluorescent light). The computersystem can then detect these signals via recorded images of the sensorplants; access a reporter model linking sensor plant signals to stressorpressures to identify the stressor pressure signaled by each sensorplant; and, in response to identifying a low pH signal, identify aparticular course of action based on the low pH level; and prompt afarmer or crop manager to apply an agricultural lime to soil to raisethe pH level of the soil in preparation for their next crop rotation.

Additionally, the computer system can prompt the farmer to perform anadditional course of action when regular crops are planted, based onsoil health as signaled by the cover crop before the regular crop isplanted. Therefore, sensor plants can be planted during “off-seasons” orin between regular crops to monitor soil conditions and prompt farmersto execute particular courses of action in order to improve soilconditions in preparation for planting regular crops based on soilconditions as monitored by the sensor plants.

2. Second Method

As shown in FIG. 3A, a second method S200 for identifying stressors incrops based on fluorescence of sensor plants includes: accessing a setof spectral images of a sensor plant sown in a crop in Block S210, thesensor plant of a sensor plant type including a set of promoters and aset of reporters configured to signal a set of stressors present at thesensor plant, the set of promoters and set of reporters forming a set ofpromoter-reporter pairs; accessing a reporter model linkingcharacteristics extracted from the spectral image of the sensor plant tothe set of stressors based on signals generated by the set ofpromoter-reporter pairs in the sensor plant type in Block S220; andidentifying a first stressor, in the set of stressors, present at thesensor plant based on the reporter model and characteristics extractedfrom the set of spectral images in Block S230.

In one variation, as shown in FIG. 3B, the second method S200 furtherincludes: estimating a nominal upwelling light spectrum based on thedownwelling light spectrum represented in the first spectral image inBlock S218, the nominal upwelling light spectrum representingreflectance and fluorescence of the sensor plant, absent the firststressor, in the presence of light according to the downwelling lightspectrum at the first time. In this variation, identifying the firststressor in Block S230 includes: extracting a first intensity, at afirst wavelength, in the upwelling light spectrum represented in thesecond spectral image in Block S232; extracting a first nominalintensity, at the first wavelength, in the nominal upwelling lightspectrum in Block S234; calculating a first deviation between the firstintensity and the first nominal intensity at the first wavelength inBlock S236; and, in response to the first deviation exceeding athreshold deviation, predicting presence of the first stressor at thesensor plant in Block S238.

In one variation, as shown in FIG. 3A, the second method S200 furtherincludes: isolating a first action, in a set of actions defined for thesensor plant type, linked to the first stressor in Block S240; and inresponse to identifying the first stressor, prompting a farmer toperform the first action at the crop to mitigate the first stressor inBlock S250.

In one variation, the second method S200 includes: accessing a firstspectral image of a sensor plant sown in a crop in Block S212, the firstspectral image depicting a downwelling light spectrum and captured, at afirst time, by an optical spectrometer defining a field of view facingopposite the sensor plant, the sensor plant of a sensor plant typeconfigured to signal a set of stressors present at the sensor plant;accessing a second spectral image of a sensor plant sown in a crop inBlock S214, the second spectral image depicting an upwelling lightspectrum captured at approximately the first time, by the opticalspectrometer defining the field of view facing the sensor plant;accessing a reporter model linking solar induced fluorescencemeasurements, extracted from the downwelling light spectrum and theupwelling light spectrum of the sensor plant, to the set of stressorsfor plants of a type of the sensor plant in Block S220; and identifyinga first stressor, in the set of stressors, present at the sensor plantbased on the reporter model and solar induced fluorescence measurementsin Block S230.

2.1 Applications

Generally, a system—such as a local or remote computer system inconjunction with a user (e.g., technician, scientist, laboratory)—canexecute Blocks of the second method S200 to identify a stressor presentat a sensor plant (and therefore present within a greater planted cropmore generally) based on signals (e.g., fluorescence in theelectromagnetic spectrum) produced by the sensor plant, which isgenetically modified to include a promoter-reporter pair configured toactivate and exhibit a signal (e.g., fluorescence) in the presence of aparticular stressor. More specifically, the computer system can: accesshyperspectral images—of a leaf area of a sensor plant, a whole sensorplant, a group of like sensor plants, a whole crop of sensor plants, ormany fields of sensor plants—recorded by a remote sensing system (e.g.,in a handheld device, in a boom or pole installed in the field, inmanned or unmanned field equipment, in an aircraft, or in a satellite);extract spectral characteristics for these hyperspectral images; andinterpret presence and/or magnitude of a particular stressor(s) presentat the sensor plant, group of plants, crop, or fields based oncorrelations between spectral characteristics extracted from thesehyperspectral images and known characteristics (e.g., fluorescence)expressed by a particular generic promoter-reporter pair in this sensorplant.

For example, the computer system can access a downwelling hyperspectralimage representing a downwelling light spectrum (i.e., solar radiationradiated downward onto land) and an upwelling hyperspectral imagerepresenting an upwelling light spectrum (i.e., electromagneticradiation reflected upwardly and electromagnetic radiation fluoresced byearth, plants, and other biomass), both recorded approximatelyconcurrently by: a mobile handheld device including a hyperspectralsensor; a fixed or mobile ground-based hyperspectral sensor (e.g.,mounted to a boom or pole installed in a field); a hyperspectral sensorarranged in an aircraft; or a satellite including a hyperspectralsensor. In a similar implementation, an imaging system (e.g., an RGBcamera, a multispectral or hyperspectral imaging system) can capturedigital images (e.g, RGB images, spectral images, hyperspectral images,multispectral images) of a plant canopy, such as including exclusivelysensor plants or a combination of both sensor plants and nearbynon-sensing plants. For example, the imaging system can include: anoptomechanical fore optic that supports measurement of fluorescent andnon-fluorescent targets; and a digital spectrometer sensor or digitalcamera sensor that records images through the optomechanical fore optic,as shown in FIG. 6 . The imaging system can also: captureelectromagnetic radiation inbound from opposing directions (e.g., upwardto capture downwelling solar radiation and downward to capture upwellingreflected and fluoresced radiation) in one hyperspectral image; and thensplit this hyperspectral image into discrete, concurrent downwelling andupwelling hyperspectral images. Alternatively, the imaging system: caninclude an electromechanical motion system configured to rapidly changethe field of view of the digital spectrometer sensor; can capture adownwelling hyperspectral image; and can then trigger theelectromechanical motion system to capture an upwelling hyperspectralimage soon after capturing the downwelling hyperspectral image.

The computer system can then: extract downwelling and upwelling spectralcharacteristics from these hyperspectral images; predict a nominalfluorescence spectrum of earth, plants, and biomass based on biologyfluorescence models; and subtract the downwelling spectralcharacteristics and the nominal fluorescence spectrum from the upwellingspectral characteristics to calculate a composite spectrum thatrepresents intensities of wavelengths of light likely fluoresced by asensor plant(s) depicted in the upwelling hyperspectral image. Thecomputer system can then: retrieve a reporter model that predicts aparticular wavelength (or a narrow range of wavelengths) ofelectromagnetic radiation fluoresced by the sensor plant when a reportergene in the sensor plant expresses responsive to activation of a linkedpromoter gene in the presence of a particular stressor; extract anintensity of electromagnetic radiation in the particular wavelength (ora narrow range of wavelengths)—of fluoresced electromagnetic radiationpredicted by the reporter model—from the reporter model; and thentransform this extracted intensity into a prediction of presence of thesensor plant represented in the upwelling hyperspectral image based onparameters in the reporter model (e.g., if the extracted intensityexceeds a threshold intensity defined by the reporter model).Additionally or alternatively, the computer system can transform thisextracted intensity into a predicted magnitude of presence of the sensorplant based on this reporter model.

Thus, the computer system (e.g., a remote server, a local device, acomputer network) can execute Blocks of the second method S200 to:access hyperspectral (or spectral) images of a sensor plant recorded byan imaging system; process these hyperspectral images to detect a signalexpressed by a reporter gene in the sensor plant—but not visuallydiscernible by a human—when triggered by a corresponding promoter geneactivated by a particular stressor affecting the plant; and theninterpret this signal as presence (and/or magnitude, duration) orabsence of this particular stressor in this sensor plant, a cluster ofplants; a crop; or a greater land area or geographic region. Thecomputer system can then notify the user of presence (and/or magnitude,duration) of a detected stressor and/or prompt the user to execute aparticular action in order to reduce or eliminate the stressor wellbefore (e.g., weeks before) the stressor damages the sensor plant (andnearby plants) to a degree visually discernible by a human, at whichtime such damage may be otherwise irrecoverable and reduce or eliminateyield from this sensor plant (and/or nearby plants). For example, thecomputer system can transmit notifications or prompts directly to theuser's mobile device (e.g., smartphone) or by writing notifications orprompts to an alert feed accessible to the user.

Therefore, the computer system can execute Blocks of the second methodS200: to remotely detect early presence (and/or magnitude, duration) ofa stressor at a particular sensor plant or at a group of plants, in acrop or field, in a land area or geographic region including one or moresensor plants; and to notify a user of presence of this stressor beforethis stressor substantively reduces viability or yield of this sensorplant, group, crop, or land area.

2.2 Promoter-Reporter Pair

A sensor plant can be genetically modified to include promoter andreporter pairs that indicate presence of stressors in the sensor plant.To detect presence of these stressors, a reporter that expresses acertain signal can be coupled to the promoter of choice, each promoterlinked to a particular stressor. More specifically, the reporter caninitiate a metabolic change in the sensor plant such that a detectablesignal is produced (e.g., fluorescence). Therefore, when the sensorplant's cells express the promoter associated with a particularstressor, the reporter tagged to the promoter is also expressed andproduces a detectable signal. For example, the sensing plant can begenetically modified to fluoresce (i.e., absorb photons at one frequencyand emit photons at a different frequency) in the presence of (andproportional to) a disease or stressor. In this example, the sensingplant can be modified to fluoresce in the presence of one or moredisease or other stress pressures, such as: fungi; bacteria; nematodes;parasites; viruses; insects; heat; water stress; nutrient stress; orphytoplasmal disease.

The promoter-reporter pair can be configured according to the thirdmethod S300 described below to produce a measurable signal by pairingthe reporter with the promoter, such that when the promoter expressesthe reporter also expresses. More specifically, in the presence of aparticular stressor, the promoter gene can activate, thereby triggeringthe corresponding reporter to express a measurable signal (e.g.,fluorescence) that is distinguishable by the computer system based on acomparison of downwelling solar radiation spectra and upwellingelectromagnetic radiation spectra reflected by the sensor plant andother nearby biomass. Based on this measurable signal, the computersystem can predict stressors present at sensor plants including thepromoter-reporter pair. For example, the promoter-reporter pair can beconfigured to generate a fluorescence signal exhibiting a highsignal-to-noise ratio to reduce effects of variations in downwellingsolar radiation (e.g., due to clouds) and variations of biomassreflectance on stressor predictions. The computer system can thus accessa set of hyperspectral images—depicting solar spectra (e.g., downwellinglight spectra) and reflected and fluoresced light spectra (e.g.,upwelling light spectra)—of the sensor plant, extract this signal (e.g.,intensity of a particular wavelength or wavelength band in theelectromagnetic spectrum) from this hyperspectral image, and interpretpresence of this stressor based on this signal. For example, thecomputer system can extract fluorescence generated by thepromoter-reporter pair from hyperspectral images (e.g., downwellinglight spectra and upwelling light spectra) of the sensor plant. Based onthe fluorescence signal generated by the sensor plant (e.g., wavelengthand intensity of fluorescence), the computer system can identify aparticular reporter associated with the fluorescence signal andtherefore identify a particular promoter-reporter pair. Because thepromoter is associated with a particular stressor, the computer systemcan identify a particular stressor present at the sensor plant assignaled by the sensor plant.

In one example, the computer system can access (e.g., via a computingdevice associated with the user) a set of hyperspectral images of asensor plant genetically modified to include: a first promoter-reporterpair, in a set of promoter-reporter pairs, configured to fluoresce, at afirst intensity, at a first wavelength, in response to presence of thefirst stressor at the sensor plant; and a second promoter-reporter pair,in the set of promoter-reporter pairs, configured to fluoresce, at asecond intensity, at a second wavelength, in response to presence of thesecond stressor at the sensor plant. In this example, the computersystem can identify the first stressor present at the sensor plant basedon fluorescence of the sensor plant, at the first intensity, at thefirst wavelength.

2.3 Solar Induced Fluorescence

A user (e.g., technician, scientist, laboratory) can genetically modifya sensor plant to generate solar induced fluorescence in the presence ofparticular stressors by genetically modifying the sensor plant toinclude promoter-reporter pairs. Fluorescence is a process in whichphotons are absorbed by molecules at one frequency and emitted by thesemolecules at a different frequency. In particular, solar inducedfluorescence (or “SIF”) in plants is the reemission, at a longerwavelength, of solar photons absorbed by pigments in a plant. A user canisolate solar induced fluorescence produced by a sensor plant in a cropof plants in order to identify stressors present at the sensor plant.

To measure fluorescence of a sensor plant, a user can extract solarinduced fluorescence measurements from hyperspectral images captured byan optical spectrometer. Hyperspectral images may depict upwelling lightspectra and/or downwelling light spectra. The computer system canextract features from these spectra to determine fluorescence of thesensor plant, and therefore to determine whether a stressor presenceexists at the sensor plant.

Fraunhofer lines represent wavelengths or narrow ranges of wavelengthsat which the solar spectrum exhibits sharp decreases in intensity in theelectromagnetic spectrum, as shown in FIGS. 7A and 7B. In one variation,the computer system can identify stressors present at the sensor plantbased on changes in intensity at these Fraunhofer lines. Alternatively,the computer system can measure changes in intensity at Telluric lines.Therefore, at these wavelengths or wavelength bands (e.g. range ofwavelengths), the computer system can distinguish between fluorescencegenerated by the sensor plant and other components of upwelling light.

2.3.1 Downwelling Light and Upwelling Light

A user can access hyperspectral images of a sensor plant in order toidentify stressors present at the sensor plant. In particular, thecomputer system can access hyperspectral images depicting downwellinglight spectra and upwelling light spectra of the sensor plant andextract characteristics of these spectra in order to identify stressorspresent at the sensor plant. A remote sensing system can capture thesehyperspectral images depicting downwelling light and upwelling light atthe sensor plant such that the computer system can remotely access thesehyperspectral images via a computing device associated with the user forinterpretation. For example, the computer system can access: a firsthyperspectral image depicting a downwelling light spectrum and captured,at a first time, by an optical spectrometer defining a field of viewopposite the sensor plant; and a second hyperspectral image depicting anupwelling light spectrum captured, at approximately the first time, bythe optical spectrometer defining the field of view facing the sensorplant.

Downwelling light spectra captured above the sensor plant arerepresentative of solar light incident at the sensor plant. As shown inFIG. 5A, downwelling light spectra (or “solar spectra”) exhibit a finespectral structure. Upwelling light includes light both reflected fromand emitted by the sensor plant. Thus, upwelling light accounts for bothreflected light and fluorescent light. As shown in FIG. 5B, upwellinglight spectra exhibit a fine spectral structure, similar to thestructure of the downwelling light spectrum.

Upwelling light includes both reflected light and fluorescent light.While reflected light spectra exhibit the fine spectral structure of thedownwelling light, fluorescent light spectra are spectrally smooth.Reflected light is proportional to downwelling light. Therefore,reflected light spectra exhibit a similar shape to downwelling lightspectra. However, fluorescent light exhibits a spectrally smooth shape,differing from the shape of downwelling light spectra and reflectedlight spectra. Therefore, the computer system can identify stressorspresent at the sensor plant based on differences in the shapes of thedownwelling light spectrum and the upwelling light spectrum. Thecomputer system can identify changes between the fine spectral structureof a particular upwelling light spectrum and downwelling light spectrato identify presence of a stressor at the sensor plant. For example, thecomputer system can: access a first hyperspectral image depicting adownwelling light spectrum and captured, at a first time, by an opticalspectrometer defining a field of view facing opposite a sensor plant;access a second hyperspectral image depicting an upwelling lightspectrum captured, at approximately the first time (e.g., within onesecond, five seconds, one minute, etc.), by the optical spectrometerdefining the field of view facing the sensor plant; access a reportermodel linking solar induced fluorescence measurements—extracted fromdownwelling light spectra and upwelling light spectra—to the set ofstressors for plants of a type of the sensor plant; and identify a firststressor present at the sensor plant based on the reporter model andcharacteristics of the set of hyperspectral images. Thus, the computersystem can identify fluorescence of the sensor plant based ondifferences between the downwelling light spectrum and the upwellinglight spectrum, and therefore identify a stressor present at the sensorplant based on these differences.

Additionally and/or alternatively, the computer system can normalizedownwelling light spectra and upwelling light spectra captured by theremote sensor system, and therefore extract normalized features (e.g.,normalized intensities at particular wavelength ranges) from thesespectra to identify stressors at the sensor plant, based on thesenormalized features.

In one variation, the user can identify changes in the upwelling lightspectrum from the downwelling light spectrum by examining wavelengthintensities of the spectra at Fraunhofer Lines in order to identify astressor present at the sensor plant. For example, the computer systemcan: extract a normalized downwelling intensity, at a wavelength (orwavelength band) corresponding to a Fraunhofer line, from a downwellingspectrum depicted in a first hyperspectral image; extract a normalizedupwelling intensity, at the wavelength (or within the range ofwavelengths) corresponding to the Fraunhofer line in the electromagneticspectrum, from an upwelling spectrum depicted in a second hyperspectralimage; calculate a difference or ratio between the upwelling intensityand the downwelling intensity; and, in response to the differenceexceeding a threshold difference, identify a first stressor present atthe sensor plant.

In one implementation, the computer system can access an averagedownwelling light spectrum representative of a set of downwelling lightspectra captured over a first set duration (e.g., one hour, six hours,twelve hours) and an average upwelling light spectrum representative ofa set of upwelling light spectra captured over the set duration. Theremote sensing system can capture images of the sensor plant atdifferent angles and at different times throughout the day. In oneimplementation, the remote sensing system captures images of the sensorplant between 10 AM and 2 PM (e.g., when direct sunlight is maximized).

2.3.2 Nominal Upwelling Light

Upwelling light includes reflected light and fluorescence emissions. Inthe absence of fluorescence emissions (e.g., absence of a signalingsensor plant), upwelling light represents reflected light. Reflectedlight can be estimated as a fraction of downwelling light (e.g., 5o%,7o%, 9o%) at particular wavelengths based on reflectance of the sensorplant. Thus, in the absence of fluorescence, an upwelling light spectrumexhibits approximately the same structure as a corresponding (e.g., samelocation, time, day) downwelling light spectrum but with reducedintensities as a function of wavelength, accounting for absorbed andtransmitted light (e.g., light that is not reflected).

A user can develop an upwelling light model for modelling upwellinglight in the absence of fluorescence based on downwelling lightmeasurements (e.g., intensity of light at various wavelengths). Forexample, a user can: access a first hyperspectral image depicting adownwelling light spectrum at a sensor plant and access a secondhyperspectral image depicting an upwelling light spectrum recorded by ahigh-resolution spectrometer at a non-sensing plant of a first type;extract a reflected light spectrum and a baseline fluorescent lightspectrum based on the downwelling light spectrum; calculate areflectance factor based on the reflected light spectrum and thedownwelling light spectrum; and generate an upwelling light model basedon the reflectance factor and the baseline fluorescent light spectrum.The computer system can refine the upwelling light model by repeatingthis process for multiple downwelling light spectra and upwelling lightspectra to calculate an average reflectance factor and/or averagebaseline fluorescence measurements. Later, the computer system canaccess this upwelling light model to generate nominal upwelling lightspectra (e.g. expected upwelling light spectra in the absence ofstressors) according to measured downwelling light spectra. Therefore,the computer system can compare upwelling light spectra to nominalupwelling light spectra (e.g., as estimated by the upwelling lightmodel) to identify stressors present at the sensor plant.

In one implementation, the computer system can estimate nominalupwelling light spectra according to the following upwelling lightmodel:

y(λ)=a×r(λ)s(λ)+b×f(λ)   (Equation 1)

The computer system can estimate nominal upwelling light y(λ) accordingto Equation 1, where y(λ) represents the nominal upwelling light (or“expected upwelling light”) predicted at the sensor plant in the absenceof stressors, r(λ) represents the canopy reflectance (e.g., reflectanceof sensor plant and surroundings), s(λ) represents measured downwellinglight, f(λ) represents canopy fluorescence (e.g., fluorescence of sensorplant and surroundings), and a and b are intensity factors.

In one variation, the computer system can generate an upwelling lightmodel accounting for external factors included in images of the sensorplant such as other types of plants, soil, rocks, etc. For example, thecomputer system can access a set of hyperspectral images recorded from asatellite. In this example, the hyperspectral images may correspond toan entire crop rather than solely the sensor plant. Thus, the computersystem can estimate nominal upwelling light, in the absence of thestressor, for the entire crop, based on types of plants, soil, and/orother features represented in the hyperspectral images.

Generally, the computer system can, at a first time, generate anupwelling light model. Later, the computer system can access theupwelling light model to check for differences between an upwellinglight spectra recorded at the sensor plant and nominal upwelling lightspectra, estimated by the upwelling light model and based on downwellinglight spectra, in order to determine whether a pressure is present at asensor plant of the first type. For example, the computer system can:access a downwelling light spectrum and an upwelling light spectrum of asensor plant recorded by a high-resolution spectrometer; access theupwelling light model; estimate a nominal upwelling light spectrum basedon the upwelling light model and the downwelling light spectrum;calculate a deviation between an area of the upwelling light spectrumbetween a first wavelength and a second wavelength (e.g., within anarrow range of wavelengths) and an area of the model upwelling lightspectrum between the first wavelength and the second wavelength; and, inresponse to the deviation exceeding a threshold deviation, identify aparticular stressor present at the sensor plant.

2.3.3 Extract Reporter Fluorescence

In one variation, the computer system can extract a solar inducedfluorescence spectrum of a sensor plant from a downwelling lightspectrum and an upwelling light spectrum recorded at the sensor plant inorder to identify a particular stressor present at the sensor plant. Forexample, the computer system can: access an upwelling light spectrumrecorded at the sensor plant, the upwelling light spectrum a combinationof a reflected light spectrum and a measured fluorescent light spectrum;and extract a reporter fluorescent light spectrum based on the upwellinglight spectrum and the downwelling light spectrum. In this example, thecomputer system can extract the reporter fluorescent light spectrumincluding: estimating the reflected light spectrum by multiplying thedownwelling light spectrum by a reflectance factor; and estimating themeasured fluorescent light spectrum as a first difference between theupwelling light spectrum and the reflected light spectrum; andestimating the reporter fluorescent light spectrum as equivalent to themeasured fluorescent light spectrum.

The computer system can further refine this reporter fluorescent lightspectrum by accounting for fluorescence not produced by the sensor plant(e.g., fluorescence produced by other plants, soil, etc.). For example,the computer system can: access a model fluorescent light spectrumcorresponding to total fluorescence within an area of the sensor plant;calculate a second difference between the measured fluorescent lightspectrum and the model fluorescent light spectrum; and estimate thereporter fluorescent light spectrum for the sensor plant based on thedifference.

Once the user has extracted the reporter fluorescent light spectrum, thecomputer system can identify a particular reporter associated with thereporter fluorescent light spectrum and therefore identify a particularpromoter-reporter pair and particular stressor associated with thefluorescence signal produced by the sensor plant.

In one variation, the computer system can estimate reporter fluorescencefrom the upwelling light and downwelling light captured, approximatelyconcurrently, of the sensor plant, based on Fraunhofer Lines, to predictstressor presence. The computer system can estimate reporterfluorescence as a difference between measured downwelling light andmeasured upwelling light. For example, the computer system can: extracta downwelling intensity from a first hyperspectral image depicting adownwelling light spectrum, at the wavelength associated with theFraunhofer line in the electromagnetic spectrum; extract an upwellingintensity (e.g., a normalized upwelling intensity) from a secondhyperspectral image depicting an upwelling light spectrum (e.g., anormalized upwelling light spectrum), at the wavelength associated withthe Fraunhofer line in the electromagnetic spectrum; calculate adifference between the upwelling intensity and the downwellingintensity; and, in response to the difference exceeding a thresholddifference, identify the first stressor present at the sensor plant. Inthis example, the computer system can estimate reporter fluorescence asequivalent to the difference between the upwelling intensity and thedownwelling intensity.

In one variation, the computer system can estimate a reporterfluorescent light spectrum from the upwelling light spectrum and thedownwelling light spectrum. For example, the computer system can: accessa downwelling light spectrum and an upwelling light spectrum, theupwelling light spectrum representing a summation of a reflected lightspectrum and a fluorescent light spectrum; and extract a reporterfluorescent light spectrum from the upwelling light spectrum. In thisexample, to extract the reporter fluorescent light spectrum, thecomputer system can: estimate the reflected light spectrum based onreflectance factors of the sensor plant, in the presence of lightaccording to the downwelling light spectrum at the first time; estimatethe fluorescent light spectrum based on a first difference between theupwelling light spectrum and the reflected light spectrum; and estimatethe reporter fluorescent light spectrum as the fluorescent lightspectrum. Alternatively, to refine the reporter fluorescent lightspectrum, the computer system can: access a nominal fluorescent lightspectrum representative of fluorescence within the area of the sensorplant absent the first stressor, in the presence of light according tothe downwelling light spectrum at the first time; calculate a seconddifference between the fluorescent light spectrum and the nominalfluorescent light spectrum; and estimate the reporter fluorescent lightspectrum for the sensor plant based on the difference. In this example,the computer system can account for fluorescence, captured in theupwelling spectrum depicted in the hyperspectral images, generated byexternal factors, such as other fluorescing plants and soil. Therefore,the computer system can extract the fluorescent light spectrum (e.g.,total fluorescence) from the upwelling light spectrum, and then furtherextract the reporter fluorescent light spectrum (e.g., fluorescenceinitiated by the reporter in the sensor plant).

The computer system can access a reporter model linking fluorescencemeasurements of the sensor plant extracted from the set of hyperspectralimages to a particular stressor. For example, the user can extract afirst intensity, at a first wavelength, in an upwelling light spectrumdepicted in a first hyperspectral image. The user can then access areporter model linking the first intensity, at the first wavelength, topresence of a first stressor. In this example, the user can access thereporter model linking wavelength intensities to a particular stressor.In another example, the user can: extract a first intensity, at a firstwavelength, in an upwelling light spectrum depicted in a firsthyperspectral image; extract a first nominal intensity, at the firstwavelength, in a nominal upwelling light spectrum representingreflectance and fluorescence of the sensor plant, absent the firststressor, in the presence of light; calculate a first deviation betweenthe first intensity and the first nominal intensity at the firstwavelength the reporter model linking; and, in response to the firstdeviation exceeding a threshold deviation, predict presence of astressor at the sensor plant. The user can access the reporter modellinking the first deviation to a particular stressor present at thesensor plant, based on characteristics (wavelength intensities) offluorescence of the reporter. Therefore, the user can first determinepresence of a stressor, and determine the particular stressor presentbased on the reporter model.

2.4 Predicting Stressors

The computer system can extract characteristics from the set ofhyperspectral images to predict presence of stressors at the sensorplant. For example, the computer system can access a first hyperspectralimage depicting a downwelling light spectrum and a second hyperspectralimage depicting an upwelling light spectrum. Then, the computer systemcan: estimate a nominal upwelling light spectrum based on thedownwelling light spectrum represented in the first hyperspectral image,the nominal upwelling light spectrum representing reflectance andfluorescence of the sensor plant, absent the first stressor, in thepresence of light according to the downwelling light spectrum at thefirst time; extract a first intensity, at a first wavelength, in theupwelling light spectrum represented in the second hyperspectral image;extract a first nominal intensity, at the first wavelength, in thenominal upwelling light spectrum; calculate a first deviation betweenthe first intensity and the first nominal intensity at the firstwavelength; and, in response to the first deviation exceeding athreshold deviation, predict presence of the first stressor at thesensor plant. Additionally, as shown in FIG. 3C, the computer systemcan: extract a second intensity, at a second wavelength, in theupwelling light spectrum represented in the second hyperspectral image;extract a second nominal intensity at the second wavelength, in thenominal upwelling light spectrum; calculate a second deviation betweenthe second intensity and the second nominal intensity at the secondwavelength; and, in response to the second deviation exceeding thethreshold deviation, predict presence of the first stressor at thesensor plant. Therefore, the computer system can predict presence of astressor at a sensor plant based on the upwelling light spectrum, thedownwelling light spectrum, and the nominal upwelling light spectrum(e.g., as defined by the upwelling light model).

In one variation, as shown in FIGS. 3B and 3C, the computer system cancalculate a confidence score for a particular stressor representative ofthe user's confidence that the particular stressor is present at thesensor plant. For example, the computer system can: calculate a firstdeviation between a first intensity at a first wavelength in anupwelling light spectrum and a first nominal intensity at the firstwavelength in a nominal upwelling light spectrum; and calculate a firstconfidence score based on the first deviation. Then, in response topredicting presence of a first stressor based on the first deviation,the computer system can: calculate a second deviation between a secondintensity at a second wavelength in the upwelling light spectrum and asecond nominal intensity at the second wavelength in the nominalupwelling light spectrum; calculate a second confidence score based onthe first deviation and the second deviation, the second confidencescore greater than the first confidence score; and, in response to thesecond confidence score exceeding a threshold confidence score, predictpresence of the first stressor. Alternatively, in response to the seconddeviation falling below the threshold deviation, the computer systemcan: calculate a third confidence score based on the first deviation andthe second deviation, the third confidence score less than the firstconfidence score; and, in response to the third confidence score fallingbelow a threshold confidence score, predict absence of the firststressor at the sensor plant.

In one example, the computer system can calculate a first deviation of10% between a first intensity at a first wavelength in an upwellinglight spectrum and a first nominal intensity at the first wavelength ina nominal upwelling light spectrum. Then, in response to the deviationexceeding a threshold deviation, the computer system can: calculate afirst confidence score of 50% based on the first deviation; calculate asecond deviation of 10% between a second intensity at a secondwavelength in the measured upwelling light spectrum and a second nominalintensity at the second wavelength in the nominal upwelling lightspectrum; calculate a second confidence score of 90% based on the firstdeviation and the second deviation; and, in response to the confidencescore exceeding a threshold confidence score, predict presence of thefirst stressor at the sensor plant.

In one variation, in response to predicting presence of a stressor, thecomputer system can isolate an action that may mitigate the stressor,and suggest this action to a user associated with the crop including thesensor plant. For example, in response to identifying a first stressorpresent at the sensor plant, the computer system can: isolate a firstaction, in a set of actions defined for the sensor plant type, linked tothe first stressor; and transmitting a notification to perform the firstaction at the crop to mitigate the first stressor to a computing deviceof a user associated with the crop. Therefore, the computer system canalert the user of stressors present in the crop and suggest particularactions for mitigating these stressors.

2.4.1 Stressor Magnitude

In one variation, the computer system can identify a magnitude of aparticular stressor based on intensity of the upwelling light spectrumat a particular wavelength. In this variation, the computer system canidentify a particular wavelength (or range of wavelengths) at which aparticular promoter-reporter pair produces a detectable signal. Thecomputer system can then measure intensity of upwelling light at thesefrequencies to determine presence of a stressor at the sensor plant andto determine a stressor magnitude (e.g., an extent to which it ispresent). For example, the user may genetically modify a sensor plant toinclude a first promoter-reporter pair configured to signal presence ofa first stressor and to generate maximum red fluorescence atapproximately 580 nanometers in the presence of the first stressor. Uponpredicting presence of the first stressor at the sensor plant, based ona set of hyperspectral images depicting a downwelling light spectrum andan upwelling light spectrum, the computer system can measure anintensity of the upwelling light spectrum at 580 nm. In response tomeasuring a relatively high intensity, the computer system can predict arelatively high magnitude of the first stressor at the sensor plant.Alternatively, in response to measuring a relatively low intensity, thecomputer system can predict a relatively low magnitude of the firststressor at the sensor plant. Therefore, the computer system canestimate the magnitude of a particular stressor at the sensor plantbased on the strength (e.g., intensity) of the signal produced by thesensor plant.

In one implementation, the computer system can determine stressormagnitude based on intensity changes within a narrow range ofwavelengths in upwelling light. For example, the computer system can, ata first time: extract a first intensity, at a first wavelength, and asecond intensity, at a second wavelength in an upwelling light spectrumrepresented in a hyperspectral image of a sensor plant; and extract afirst nominal intensity, at the first wavelength, and a second nominalintensity, at the second wavelength, in a nominal upwelling lightspectrum. Then, the computer system can: extract a first area in theupwelling light spectrum between the first wavelength and the secondwavelength, based on the first intensity and the second intensity;extract a nominal area in the nominal upwelling light spectrum betweenthe first wavelength and the second wavelength, based on the firstnominal intensity and the second nominal intensity; calculate adifference between the first area and the nominal area; and estimate amagnitude of the first stressor present at the sensor plant proportionalto the difference. The computer system can select the first wavelengthand the second wavelength based on wavelengths at which the particularreporter of the sensor plant is expected to generate fluorescence.Therefore, the computer system can estimate the magnitude of aparticular stressor present at the sensor plant based on the strength(e.g., intensity) of the signal produced by the sensor plant over anarrow range of wavelengths corresponding to fluorescence of aparticular reporter associated with the particular stressor.

2.4.2 Detection of Promoter-Reporter Pair Signals

In one variation, the computer system can detect solar-inducedfluorescent signals by implementing narrow-wavelength measurements neardark spectral features in incident solar radiation. Narrow bandtechniques associated with Fraunhofer lines (from absorption in thesolar atmosphere) and Telluric lines (which originate from absorption ofmolecules in Earth's atmosphere) enable measurement of the opticalsignals in daylight, without implementing external illumination. Thecomputer system can extract narrow-wavelength measurements (e.g., atthese Fraunhofer lines and/or Telluric lines) from hyperspectral imagesof the sensor plant to identify fluorescent signals produced by thesensor plant. By extracting these narrow-wavelength measurements, thecomputer system can detect small, obscure signals with both specificityand accuracy, and detect these signals from hyperspectral imagescollected both on the ground and airborne. Therefore, the computersystem can detect signals produced by sensor plants in hyperspectralimages collected from a large range of distances.

The computer system can access hyperspectral images of the sensor plantcollected from close ranges. For example, the computer system can accesshyperspectral images of a sensor plant collected from tools mounted ontop of self-propelled equipment, such as a pole placed in a crop mountedwith a device for collecting images of the sensing plants, as shown inFIG. 6 . In another example, the computer system can accesshyperspectral images of the sensor plant captured manually by a farmeroperating a drone (or “UAV”) or dispatching an autonomous drone to scanregions of a crop where sensing plants are located to collect images ofthese sensing plants. In one implementation, the computer system canaccess hyperspectral images of the sensor plant captured by a sensingdevice configured to install (e.g., clamp) onto a leaf or stalk of thesensing plant and to capture close-range images of fluorescing surfaceson the sensing plant at a high frequency (e.g., once per minute, onceper hour). In these examples, the computer system can access thesehyperspectral images from a remote database, the hyperspectral imagesuploaded to the remote database via a cellular network or downloaded toa mobile device or vehicle via a local ad hoc wireless network when amobile device or vehicle is nearby, and then uploaded from the mobiledevice or vehicle to the remote database. In another implementation, thecomputer system can access hyperspectral images manually collected by afarmer on a mobile device. In this implementation, the computer systemcan access the hyperspectral images collected on the mobile device, thehyperspectral images electronically uploaded to remote storage orautomatically uploaded via a native or web-based agriculturalapplication executing on the mobile device. The computer system caninterpret pressures on this plant directly from features extracted fromthese close-range images to generate a high-resolution, short-intervaltimeseries representation of the health of this sensing plant. Thecomputer system can then combine this high-resolution, short-intervaltimeseries representation of the health of this sensing plant withfeatures extracted from low-frequency, wider field-of-view images ofclusters of plants or a whole field containing this sensing plant topredict the health of multiple or all plants in this field.

Alternatively, the computer system can access hyperspectral images ofsensor plants collected from mid-range distances to collect wavelengthmeasurements, the hyperspectral images captured from manned or unmannedvehicles. In one implementation, the computer system can accesshyperspectral images of a sensor plant captured by a farmer driving avehicle along an edge of a crop or a specific region of the crop thatcontains sensing plants, and collecting images via a handheld device ora device mounted on the farmer's vehicle. The computer system can thenaccess these hyperspectral images from the remote database, timestamped,and georeferenced, upon upload or at a later time.

In another variation, the computer system can access hyperspectralimages captured from long range distances to collect wavelengthmeasurements. The computer system can access hyperspectral images of theagricultural fields captured by long-duration, high-altitude manned orunmanned aerial vehicles, or by satellites such as OCO-2 or GOSAT. Forexample, the computer system can access satellite images of entireagricultural fields, including multiple clusters of sensing plants.These hyperspectral images can be accessed with a lower frequency and ata lower resolution than images accessed from a close-range opticalsensor such as a mobile device. Therefore, the computer system canaccess hyperspectral images collected from both long-range distances andshort-range distances.

The computer system can access hyperspectral images captured by thesevarious methods of collecting hyperspectral images of sensor plants froma range of distances and at various image resolution and extractwavelength measurements to collect high-quality data that enable rapid,targeted responses to certain plant stressors and therefore increaseyield of plants nearby in the same agricultural field. In oneimplementation, the computer system can access hyperspectral imagescaptured at a pole mounted with a high-resolution optical sensor (e.g.,a RGB camera, a multispectral camera or spectrometer, a thermal or IRcamera) and located in the center of a first cluster of sensing plantsin a crop, the optical sensor configured to capture high-resolutionimages of the sensing plants at multiple times each day and upload thehyperspectral images to a remote database. The computer system canaccess these high-resolution images from the remote database to collectstressor data for the specific cluster of sensing plants. Additionally,the computer system can access hyperspectral images collected by asatellite configured to capture low-resolution images of the entirecrop, which may include multiple sensing plant clusters, such as onceper two-week interval. The computer system can then: access thesehyperspectral images from a satellite image database; generate a modelto link behaviors of the first sensing plant cluster to the otherclusters in the crop based on the daily behavior of the first clusterand the biweekly behavior of all sensing plant clusters in the crop; andinterpolate behavior of the crop as a whole in regions with or withoutsensing plants. In another example, when the computer system calculatesa certain pressure at the first sensing plant cluster, it also signalsthe farmer or agronomist to collect a leaf or soil sample from a regionof the crop containing the sensing plant cluster, and to test the samplefor an exact pressure reading. The computer system can then access thismeasurement to link data and stressors detected by the sensing plants tothe pressure magnitude in the plants.

The computer system can access hyperspectral images of sensor plantscollected from a variety of devices, such as from a handheld camera, ahandheld spectrometer, a mobile phone, or from any other device thatincludes a high-resolution spectrometer, includes band-specificcoatings, or is otherwise configured to detect wavelengths ofelectromagnetic radiation fluoresced, luminescence, or passed by thesensing plant in the presence of a particular stressor. In onevariation, the computer system can access hyperspectral images collectedfrom a variety of instrumentation, as different instrumentation can beused depending on the compound of interest, as the wavelengths ofdifferent compounds are each best observed under different conditionsand may require distinct modes of detection.

3. Third Method

As shown in FIG. 4A, a third method S300 for method for selectingreporters for detection of stressors in crops based on fluorescence ofsensor plants includes: accessing a nominal upwelling light spectrumrepresentative of reflectance and fluorescence within an area of a cropin Block S310; extracting a nominal peak intensity, at a firstwavelength, in the nominal upwelling light spectrum for the area of thecrop in Block S312; accessing a first fluorescent light spectrumdepicting fluorescence of a first reporter gene, in a set of reporters,when expressed in Block S320; extracting a first peak intensity, at thefirst wavelength, in the first fluorescent light spectrum of the firstreporter gene in Block S322; calculating a first signal-to-noise ratioof the first peak intensity of the first reporter to the nominalintensity for the area of the crop in Block S330; and, in response tothe first signal-to-noise ratio exceeding a threshold signal-to-noiseratio, selecting the first reporter gene in Block S340. The third methodS300 further includes: pairing a first promoter gene, from a set ofpromoter genes, linked to a first stressor, in a set of stressors, withthe first reporter gene to form a first promoter-reporter pairconfigured to trigger fluorescence in the presence of the first stressorin Block S350; and genetically modifying a sensor plant to include thefirst promoter-reporter pair to configure the sensor plant to signalpresence of the first stressor in Block S360.

3.1 Applications

Generally, a system—such as a local or remote computer system inconjunction with a user (e.g., a laboratory technician, an operator)—canexecute Blocks of the third method S300 to design a sensor plant toinclude a promoter-reporter pair configured to detect a particularstressor present at the sensor plant and produce a detectable signal(e.g., in the electromagnetic spectrum) upon detection of the particularstressor. In particular, a user can genetically modify a sensor plant toinclude a promoter configured to activate in the presence of (e.g.,“linked to”) a particular stressor; and a reporter paired to thepromoter and configured to exhibit (or “express”) a signal when thepromoter is active in the sensor plant. For example, the computer systemcan cooperate with the user to genetically modify a sensor plant toactively produce a signal (e.g., actively fluoresce)—without excitationof the sensor plant—in the presence of a stressor, the signal configuredfor detection via passive remote detection. Therefore, the computersystem can cooperate with the user to genetically modify sensor plantsto include promoter-reporter pairs that generate readily detectablesignals in the presence of these stressors.

The computer system can select (or guide the user toward selecting) areporter for a particular promoter-reporter pair based on particularwavelengths or ranges of wavelengths (e.g., narrow bands) at which thereporter produces a detectable signal in a sensor plant. Morespecifically, the computer system (or the user, under guidance of thecomputer system) can select a reporter that generates a measurabledifference in an upwelling light spectrum of the sensor plant in thepresence of a stressor, when compared to a model upwelling lightspectrum representative of the sensor plant in the absence of thestressor. For example, the computer system can select (or suggest to auser) a first reporter that generates fluorescence of the sensor plantbetween 540 nanometers and 660 nanometers in the electromagneticspectrum. To increase detectability of signals produced by the sensorplant (e.g., via the reporter), the computer system can select areporter that generates fluorescence at particular wavelengths at whichsolar spectra exhibit sharp decreases in wavelength intensity. Forexample, as shown in FIGS. 7A and 7B, the computer system can select areporter that generates fluorescence of the sensor plant aboutFraunhofer Lines present in solar spectra. Alternatively, the computersystem can select a reporter that generates fluorescence of the sensorplant about Telluric Lines present in solar spectra.

In one implementation, the computer system can select reporters based ona signal-to-noise ratio of a fluorescence signal generated by a sensorplant in the presence of stressor to upwelling light captured at thesensor plant absent the stressor. For example, the computer system can:calculate a signal-to-noise ratio (e.g., at a particular wavelength,over a range of wavelengths) of fluorescence generated by the sensorplant in the presence of the stressor, the sensor plant including aparticular promoter-reporter pair, to upwelling light captured at thesensor plant in the absence of the stressor; and, in response to thesignal-to-noise ratio exceeding a threshold signal-to-noise ratio,select the particular reporter for inclusion in a firstpromoter-reporter pair. Thus, by selecting reporters that generate arelatively high signal-to-noise ratio, the computer system can enabledetection of the signal generated by the sensor plant in the presence ofa stressor.

Upon selection of a first reporter, the computer system can pair thefirst reporter with a first promoter (or suggest pairing the firstreporter with a first promoter to a user) to form a firstpromoter-reporter pair configured to detect and signal presence of afirst stressor. The computer system can select (or suggest) the firstpromoter based on a type of stressor linked with the first promoter.Once paired with the promoter, the computer system can geneticallymodify a sensor plant to include the first promoter-reporter pair, thesensor plant configured to signal presence of the first stressor at thesensor plant. Additionally, the computer system can genetically modifythe sensor plant to include multiple promoter-reporter pairs.

3.2 Promoter-Reporter Pair

A user can genetically modify a sensor plant to include apromoter-reporter pair configured to signal presence of a stressor atthe sensor plant. The computer system can: select a promoter linked to aparticular stressor for a promoter-reporter pair; select a reportercorresponding to a particular solar induced fluorescence spectrum(hereinafter “fluorescence spectrum”); and pair the promoter and thereporter (e.g. suggest pairing the promoter and the reporter to a user)to form a promoter-reporter pair. Thus, the computer system can select apromoter-reporter pair (e.g. suggest a promoter-reporter pair to a user)for genetically modifying a sensor plant to include thepromoter-reporter pair, the sensor plant configured to fluoresce in thepresence of the particular stressor.

The sensor plant can include a promoter-reporter pair configured tosignal presence of particular biotic and/or abiotic pressuresexperienced by the sensor plant, such as pest, disease, water, heat,soil health, and/or nutrient stresses or deficiencies. For example, thesensor plant can be genetically modified to include a promoter withactivity linked to presence of one stressor at the plant, such as afungal, pest, heat, water, disease, or nutrient stress. The sensor plantcan also be genetically modified to include a reporter paired with thepromoter and configured to produce a detectable signal—such as anelectromagnetic signal in the visible light or infrared spectrum—whenthe corresponding promoter is activated. For example, the reporter inthe sensor plant can be configured to fluoresce (i.e., produce a signalin the visible spectrum) when the corresponding promoter is active inthe sensor plant. More specifically, a promoter-reporter pair can beincorporated into the sensor plant via molecular binding and metabolicengineering techniques that associate expression of a promoterresponsive to a particular biological stress with a reporter thatproduces a measurable signal when the promoter expresses. Thepromoter-reporter pair can be configured to produce a measurable signalby pairing the reporter with the promoter such that when the promoterexpresses the reporter also expresses. Therefore, via expression of thereporter, the promoter-reporter pair can produce a measurable signal ofa particular biological stress or trait in the sensor plant.

The computer system can pair promoters and reporters to form a set ofpromoter-reporter pairs. The computer system can selectpromoter-reporter pairs based on detectability of signals generated byreporters and suggest these promoter-reporter pairs to a user forinclusion in genetically modified sensor plants. To select reporters,the computer system can compare fluorescence generated by reporters tonominal upwelling light. In one example, the computer system can: accessa nominal upwelling light spectrum representative of reflectance andfluorescence within an area of a crop; extract a nominal peak intensity,at a first wavelength, in the nominal upwelling light spectrum for thearea of the crop; access a fluorescent light spectrum corresponding to ared-fluorescence protein; extract a first fluorescent light spectrumdepicting fluorescence of the red-fluorescence protein, when expressed;and, in response to a first signal-to-noise ratio between the first peakintensity and the first nominal intensity exceeding a thresholdsignal-to-noise ratio, select the first reporter gene. Then, thecomputer system can: pair a first promoter linked to plant dehydrationto the red-fluorescence protein to form the first promoter-reporterpair; and genetically modify the sensor plant to include the firstpromoter-reporter pair, the sensor plant configured to fluoresce at thefirst intensity at the first wavelength in response to dehydration ofthe sensor plant.

3.3 Nominal Upwelling Light

The computer system can access a nominal upwelling light spectrum toenable selection of reporters for promoter-reporter pairs, the nominalupwelling light spectrum representative of upwelling light at a sensorplant or within an area surrounding a sensor plant, absent stressors. Inone variation, the computer system can access the nominal upwellinglight spectrum to find regions of the electromagnetic spectrum at whicha reporter generated fluorescence signal in the presence of a stressormay exhibit a high signal-to-noise ratio compared to nominal upwellinglight in the absence of the stressor.

The computer system can generate a nominal upwelling light spectrum thataccounts for reflected light (e.g., as a function of downwelling light),plant fluorescence (e.g., in the absence of a stressor), andfluorescence of other environmental factors (e.g., other plants, soil).Therefore, the computer system can generate a set of nominal upwellinglight spectra, each corresponding to a unique environment (e.g.,geographic region, area within a crop, etc.)

The computer system can access the nominal upwelling light spectrum whenselecting reporters for detection of stressors at the sensor plant. Forexample, the computer system can: access a nominal upwelling lightspectrum representative of reflectance and fluorescence within an areaof a crop; extract a nominal peak intensity, at a first wavelength, inthe nominal upwelling light spectrum for the area of the crop; access afirst fluorescent light spectrum depicting fluorescence of a firstreporter gene, in a set of reporters, when expressed; extract a firstpeak intensity, at the first wavelength, in the first fluorescent lightspectrum of the first reporter gene; calculate a signal-to-noise ratioof the first peak intensity of the first reporter to the nominalintensity for the area of the crop; and, in response to the firstsignal-to-noise ratio exceeding a threshold signal-to-noise ratio,select the first reporter gene. Therefore, the computer system canaccess the nominal upwelling light spectrum to check detectability of aparticular reporter.

3.4 Fluorescent light Spectrum

The computer system can access fluorescent light spectra correspondingto particular reporters in order to select reporters forpromoter-reporter pairs. For example, the computer system can access: afirst fluorescent light spectrum depicting fluorescence of a firstreporter gene, in a set of reporters, when expressed; a secondfluorescent light spectrum depicting fluorescence of a second reportergene, in the set of reporters, when expressed; and a third fluorescentlight spectrum depicting fluorescence of a third reporter gene, in a setof reporters, when expressed. The computer system can extractcharacteristics of these fluorescent light spectra to determine whethera particular reporter is detectable.

The computer system can compare detectable characteristics of afluorescent light spectrum of a particular reporter to detectablecharacteristics of a nominal upwelling light spectrum to determinedetectability of a particular reporter. For example, the computer systemcan: access a first fluorescent light spectrum depicting fluorescence ofa first reporter gene, in a set of reporters, when expressed; andextract a first peak intensity, at a first wavelength, in the firstfluorescent light spectrum of the first reporter gene. The computersystem can then select the first reporter based on the first peakintensity at the first wavelength. Additionally, the computer system canselect a particular wavelength or bands of wavelengths (e.g. range ofwavelengths) at which to extract the peak intensity of the fluorescentlight spectrum. For example, the computer system can extract a firstpeak intensity, at a first wavelength corresponding to a Telluric linein a nominal upwelling light spectrum, in the first fluorescent lightspectrum of the first reporter gene. Therefore, the computer system canselect reporters for promoter-reporter pairs based on detectability of asignal generated by the reporter in comparison to nominal upwellinglight.

3.5.1 Signal-to-Noise Ratio

A user (e.g., technician, scientist, laboratory, etc.) may select areporter based on wavelengths at which the sensor plant will fluorescein the presence of a particular pressure. More specifically, the usermay select a reporter that fluoresces at a particular wavelength (or aparticular range of wavelengths) and at a particular intensity in thepresence of a stressor, such that fluorescence generated by the sensorplant including the reporter is distinguishable from fluorescencegenerated by other environmental factors (e.g., other plants, soil,rocks).

In one implementation, the user may compare intensities between peaks ofthe same wavelength in a fluorescent light spectrum of a reporter and ina nominal upwelling light spectrum representative of upwelling light atthe sensor plant absent a stressor. In this implementation, the user mayselect the reporter for a sensor plant based on a high signal-to-noiseratio between the intensity of a first peak in the fluorescent lightspectrum of the reporter and the intensity of a nominal peak in thenominal upwelling light spectrum, the first peak and the nominal peak atthe same wavelength. For example, the computer system can: access anominal upwelling light spectrum representative of reflectance andfluorescence within an area of a crop; extract a nominal peak intensity,at a first wavelength, in the nominal upwelling light spectrum for thearea of the crop; access a first fluorescent light spectrum depictingfluorescence of a first reporter gene, in a set of reporters, whenexpressed; extract a first peak intensity, at the first wavelength, inthe first fluorescent light spectrum of the first reporter gene;calculate a first signal-to-noise ratio of the first peak intensity ofthe first reporter to the nominal intensity for the area of the crop;and, in response to the first signal-to-noise ratio exceeding athreshold signal-to-noise ratio, select the first reporter gene. Thecomputer system can then pair (e.g. suggest pairing to the user) thefirst reporter with a first promoter linked to a first stressor (e.g.,plant dehydration) to form a first promoter-reporter pair configured tosignal presence of the first stressor and enable a user to geneticallymodify a sensor plant to include the first promoter-reporter pair. Thus,by selecting the first promoter-reporter pair, the computer system canenable a user to genetically modify the sensor plant to signal presenceof the first stressor.

Additionally, in one variation, as shown in FIG. 4A, the computer systemcan check the signal-to-noise ratio within a narrow band of wavelengths,by calculating the signal-to-noise ratio at additional wavelengths(e.g., at a second wavelength). For example, in response to the firstsignal-to-noise ratio exceeding a threshold signal-to-noise ratio, thecomputer system can: extract a second nominal peak intensity in BlockS314, at a second wavelength, in the nominal upwelling light spectrumfor the area of the crop; extract a second peak intensity in Block S324,at the second wavelength, in the first fluorescent light spectrum of thefirst reporter gene; calculate a second signal-to-noise ratio of thesecond intensity of the first reporter gene to the nominal intensity forthe area of the crop in Block S332; and, in response to the secondsignal-to-noise ratio exceeding the threshold signal-to-noise ratio,select the first reporter gene. Therefore, the computer system can checkthat the reporter generates a signal that is detectable across a rangeof wavelengths.

3.7 Multiple Promoter-Reporter Pairs

In one implementation, the computer system can select multiplepromoter-reporter pairs for inclusion in a particular sensor plant. Forexample, the computer system can initially select a first reporter, in aset of reporters, for inclusion in a sensor plant based on a firstsignal-to-noise ratio between upwelling light in the presence of a firststressor (e.g., including fluorescence generated by the reporter) andupwelling light in the absence of the first stressor, the first reporterpaired with a first promoter to form a first promoter-reporter pairconfigured to signal presence of the first stressor. Then, the computersystem can: select a second reporter; combine the second promoter linkedto a second stressor with the second reporter to form a secondpromoter-reporter pair configured to signal presence of the secondstressor; and genetically modify the first promoter-reporter pair andthe second promoter-reporter pair, the sensor plant configured to signalpresence of the first stressor and the second stressor at the sensorplant.

The computer system can select multiple reporters based on a calculatedsignal-to-noise ratio with the model upwelling light spectrum asdescribed above, and/or based on minimizing overlapping signals betweenreporters. For example, as shown in FIG. 4B, in response to selecting afirst reporter exhibiting a maximum signal-to-noise ratio at a firstwavelength, the computer system can access a fluorescent light spectrumcorresponding to a second reporter. Then, in response to the fluorescentlight spectrum exhibiting a peak at a second wavelength, the secondwavelength a minimum distance from the first wavelength, the computersystem can: calculate a signal-to-noise ratio of an intensity of thepeak in the fluorescent light spectrum at a second wavelength to anominal intensity of a nominal upwelling light spectrum at the secondwavelength (e.g., in the absence of any stressor); and, in response tothe second signal-to-noise ratio exceeding the threshold signal-to-noiseratio, select the second reporter.

In one example, the computer system can genetically modify the sensorplant to include: a first promoter-reporter pair configured to fluoresceat a first wavelength at a first intensity in response to presence of afirst stressor; and a second promoter-reporter pair configured tofluoresce at a second wavelength at a second intensity in response topresence of a second stressor.

The computer system can pair each selected reporter with a particularpromoter to form promoter-reporter pairs configured to detect and signalthe presence of a set of stressors. In one variation, the computersystem can: select a first promoter linked to a first stressor forpairing with a first reporter to form a first promoter-reporter pair;select a second promoter linked to a second stressor for pairing with asecond reporter to form a second promoter-reporter pair; and geneticallymodify a sensor plant to include the first promoter-reporter pair andthe second promoter-reporter pair, the sensor plant configured to signalpresence of the first stressor and the second stressor at the sensorplant. For example, the computer system can: select a first promoterlinked to a disease pressure and pair the first promoter with the firstreporter to form a first promoter-reporter pair; select a secondpromoter linked to a bacterial pressure and pair the second promoterwith a second reporter to form a second promoter-reporter pair; andgenetically modify the sensor plant to include the firstpromoter-reporter pair and the second promoter-reporter pair, the sensorplant configured to signal presence of the disease pressure and thebacterial pressure at the sensor plant.

The computer systems and methods described herein can be embodied and/orimplemented at least in part as a machine configured to receive acomputer-readable medium storing computer-readable instructions. Theinstructions can be executed by computer-executable componentsintegrated with the application, applet, host, server, network, website,communication service, communication interface,hardware/firmware/software elements of a user computer or mobile device,wristband, smartphone, or any suitable combination thereof. Othersystems and methods of the embodiment can be embodied and/or implementedat least in part as a machine configured to receive a computer-readablemedium storing computer-readable instructions. The instructions can beexecuted by computer-executable components integrated bycomputer-executable components integrated with apparatuses and networksof the type described above. The computer-readable medium can be storedon any suitable computer readable media such as RAMs, ROMs, flashmemory, EEPROMs, optical devices (CD or DVD), hard drives, floppydrives, or any suitable device. The computer-executable component can bea processor but any suitable dedicated hardware device can(alternatively or additionally) execute the instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the embodiments of the invention without departing fromthe scope of this invention as defined in the following claims.

I claim:
 1. A method for monitoring stressor presence in plantscomprising: accessing a first image, in a set of images, of a set ofsensor plants sown in an environment and of a sensor plant typeconfigured to signal presence of a first stressor in a set of stressors;accessing a reporter model linking characteristics of images of sensorplants of the sensor plant type to presence of the set of stressorsbased on signals expressed by sensor plants of the sensor plant type;and interpreting presence of the first stressor at the set of sensorplants based on the reporter model and characteristics of the firstimage.
 2. The method of claim 1: wherein accessing the first image ofthe set of sensor plants configured to signal presence of the firststressor comprises accessing the first image of the set of sensor plantscomprising: a first promoter, in a set of promoters, configured toexpress responsive to presence of the first stressor at sensor plants ofthe sensor plant type; a first reporter, in a set of reporters, linkedto the first promoter and configured to generate a fluorescence signal,within a target wavelength range, responsive to expression of the firstpromoter; and wherein interpreting presence of the first stressor at theset of sensor plants based on the reporter model and characteristics ofthe first image comprises interpreting presence of the first stressor atthe set of sensor plants based on the reporter model and fluorescencemeasurements extracted from the first image.
 3. The method of claim 1:wherein accessing the first image of the set of sensor plants of thesensor plant type configured to signal presence of the first stressorcomprises accessing the first image of the set of sensor plants of thesensor plant type configured to express fluorescence signalsrepresenting presence of the first stressor; wherein accessing thereporter model linking characteristics of images of sensor plants of thesensor plant type to presence of the set of stressors based on signalsexpressed by sensor plants of the sensor plant type comprises accessingthe reporter model linking characteristics of images of sensor plants ofthe sensor plant type to presence of the set of stressors based onfluorescence signals expressed by sensor plants of the sensor planttype; and wherein interpreting presence of the first stressor at the setof sensor plants based on the reporter model and characteristics of thefirst image comprises interpreting presence of the first stressor at theset of sensor plants based on the reporter model and fluorescencemeasurements extracted from the first image.
 4. The method of claim 3:wherein accessing the first image of the set of sensor plants of thesensor plant type configured to express fluorescence signalsrepresenting presence of the first stressor comprises accessing thefirst image of the set of sensor plants of the sensor plant typeconfigured to express fluorescence signals within a first wavelengthrange and representing presence of the first stressor; and whereininterpreting presence of the first stressor at the set of sensor plantsbased on the reporter model and fluorescence measurements extracted fromthe first image comprises: extracting a first intensity, within thefirst wavelength range, of fluorescence expressed by the set of sensorplants based on characteristics of the first image; and interpretingpresence of the first stressor at the set of sensor plants based on thefirst intensity.
 5. the method of claim 4, wherein accessing the firstimage of the set of sensor plants of the sensor plant type configured toexpress fluorescence signals, within the first wavelength range,representing presence of the first stressor comprises accessing thefirst image of the set of sensor plants of the sensor plant typeconfigured to express fluorescence signals within the first wavelengthrange and representing presence of the first stressor, the firstwavelength range corresponding to a first spectral absorption line in aset of spectral absorption lines.
 6. The method of claim 1: whereinaccessing the first image of the set of sensor plants configured tosignal presence of the first stressor comprises accessing the firstimage of the set of sensor plants configured to express fluorescencesignals, in a first wavelength range, representing presence of the firststressor, the first image captured during a first time period: whereininterpreting presence of the first stressor at the set of sensor plantsbased on the reporter model and characteristics of the first imagecomprises: interpreting a first fluorescence signal of a first intensitywithin the first wavelength range based on characteristics of the firstimage; and in response to the first intensity exceeding a thresholdintensity, interpreting a pressure of the first stressor at the set ofsensor plants during the first time period; and further comprising:accessing a second image of the set of sensor plants and captured duringa second time period; interpreting a second fluorescence signal of asecond intensity within the first wavelength range based oncharacteristics of the second image; and in response to the secondintensity falling below the threshold intensity, interpreting absence ofthe first stressor at the set of sensor plants during the second timeperiod.
 7. The method of claim 1: wherein accessing the first image ofthe set of sensor plants of the sensor plant type configured to signalpresence of the first stressor comprises accessing the first image ofthe set of sensor plants of the sensor plant type configured to signalpresence of the first stressor and a second stressor in the set ofstressors; wherein accessing the reporter model linking characteristicsof images of sensor plants of the sensor plant type to presence of theset of stressors based on signals expressed by sensor plants of thesensor plant type comprises accessing the reporter model linkingcharacteristics of images of sensor plants of the sensor plant type topresence of the first stressor and the second stressor based on signalsexpressed by sensor plants of the sensor plant type; and whereininterpreting presence of the first stressor at the set of sensor plantsbased on the reporter model and characteristics of the first imagecomprises: interpreting presence of the first stressor at the set ofsensor plants based on the reporter model and a first subset ofcharacteristics of the first image; and interpreting presence of thesecond stressor at the set of sensor plants based on the reporter modeland a second subset of characteristics of the first image.
 8. The methodof claim 1: wherein accessing the first image comprises accessing thefirst image depicting an upwelling light spectrum and captured by anoptical sensor defining a first field of view facing the set of sensorplants; wherein accessing the reporter model linking characteristics ofimages of sensor plants of the sensor plant type to presence of the setof stressors comprises accessing the reporter model linking solarinduced fluorescence measurements, extracted from light spectra ofsensor plants of the sensor plant type, to presence of the set ofstressors; and wherein interpreting presence of the first stressor basedon the reporter model and characteristics of the first image comprisesinterpreting presence of the first stressor based on the reporter modeland solar induced fluorescence measurements extracted from the upwellinglight spectrum.
 9. The method of claim 8: wherein accessing the firstimage, in the set of images, comprises: accessing the first imagedepicting the upwelling light spectrum and captured by the opticalsensor defining the first field of view facing the set of sensor plants;and accessing a second image, in the set of images, depicting adownwelling light spectrum and captured by the optical sensor defining asecond field of view facing opposite the set of sensor plants; whereinaccessing the reporter model linking solar induced fluorescencemeasurements, extracted from light spectra of sensor plants of thesensor plant type, to presence of the set of stressors comprisesaccessing the reporter model linking solar induced fluorescencemeasurements, extracted from upwelling light spectra and downwellinglight spectra of sensor plants of the sensor plant type, to presence ofthe set of stressors; and wherein interpreting presence of the firststressor based on the reporter model and solar induced fluorescencemeasurements extracted from the upwelling light spectrum comprisesinterpreting presence of the first stressor based on the reporter modeland solar induced fluorescence measurements extracted from the upwellinglight spectrum and the downwelling light spectrum.
 10. The method ofclaim 1: wherein accessing the first image, in the set of images,comprises: accessing the first image depicting an upwelling lightspectrum and captured by a subset of optical sensors, in a set ofoptical sensors, defining a first field of view facing the set of sensorplants, the upwelling light spectrum representing reflectance andfluorescence of the set of sensor plants; and accessing a second image,in the set of images, depicting a downwelling light spectrum andcaptured by a second subset of optical sensors, in the set of opticalsensors, defining a second field of view facing opposite the set ofsensor plants; and wherein interpreting presence of the first stressorbased on the reporter model and characteristics of the first imagecomprises interpreting presence of the first stressor based on thereporter model and characteristics of the upwelling light spectrum andthe downwelling light spectrum, comprising: estimating a nominalupwelling light spectrum, representing nominal reflectance and nominalfluorescence of the set of sensor plants absent the first stressor,based on the downwelling light spectrum; accessing a first intensity offluorescence at a first wavelength represented in the upwelling lightspectrum; accessing a first nominal intensity of fluorescence at thefirst wavelength represented in the nominal upwelling light spectrum;characterizing a difference between the first intensity and the firstnominal intensity; and interpreting presence of the first stressor basedon the reporter model and the difference.
 10. method of claim 10,wherein characterizing the difference between the first intensity andthe first nominal intensity comprises: accessing a second intensity offluorescence at a second wavelength represented in the upwelling lightspectrum; accessing a second nominal intensity of fluorescence at thesecond wavelength represented in the nominal upwelling light spectrum;estimating a first area under a curve of the upwelling light spectrum,between the first wavelength and the second wavelength, based on thefirst intensity and the second intensity; estimating a nominal areaunder a curve of the nominal upwelling light spectrum, between the firstwavelength and the second wavelength, based on the first nominalintensity and the second nominal intensity; and characterizing thedifference between the first area and the nominal area.
 12. The methodof claim 1: wherein accessing the first image of the set of sensorplants comprises accessing the first image of the set of sensor plantsgenetically modified to include: a first promoter-reporter pair, in aset of promoter-reporter pairs, configured to express fluorescencewithin a first wavelength range responsive to presence of the firststressor at the set of sensor plants; and a second promoter-reporterpair, in the set of promoter-reporter pairs, configured to expressfluorescence within a second wavelength range responsive to presence ofa second stressor, in the set of stressors, at the set of sensor plants;wherein interpreting presence of the first stressor at the set of sensorplants comprises interpreting presence of the first stressor at the setof sensor plants based on fluorescence measurements, within the firstwavelength range, extracted from the first image; and further comprisinginterpreting presence of the second stressor at the set of sensor plantsbased on fluorescence measurements, within the second wavelength range,extracted from the first image.
 13. The method of claim 12, whereinaccessing the first image of the set of sensor plants geneticallymodified to include the first promoter-reporter pair and the secondpromoter-reporter pair comprises accessing the first image of the set ofsensor plants genetically modified to include: the firstpromoter-reporter pair configured to express fluorescence within thefirst wavelength range responsive to presence of the first stressorcomprising a pest stressor; and the second promoter-reporter pairconfigured to express fluorescence within the second wavelength rangeresponsive to presence of the second stressor comprising a nutrientstressor.
 14. The method of claim 1, further comprising, in response tointerpreting presence of the first stressor: selecting a first action,in a set of actions, configured to mitigate presence of the firststressor in plants; generating a notification comprising a prompt toexecute the first action within the environment; and transmitting thenotification to a computing device of a user affiliated with theenvironment.
 15. A method for selecting reporters for detection ofstressors in plants comprising: accessing a nominal upwelling lightspectrum representative of nominal reflectance and nominal fluorescencewithin a region of an environment; accessing a first nominal peakintensity, at a first wavelength, in the nominal upwelling lightspectrum; accessing a first fluorescent light spectrum depictingfluorescence of a first reporter gene in a set of reporter genes;accessing a first peak intensity, at the first wavelength, in the firstfluorescent light spectrum; characterizing a difference between thefirst peak intensity and the first nominal peak intensity; and inresponse to the difference exceeding a threshold difference: accessing atarget stressor, in a set of stressors, defined for sensor plants of asensor plant type; and pairing the first reporter gene with a firstpromoter gene, in a set of promoter genes, to form a firstpromoter-reporter pair configured to transiently express fluorescencesignals, at the first wavelength, responsive to presence of the targetstressor at sensor plants of the sensor plant type.
 16. The method ofclaim 15: wherein characterizing the difference between the first peakintensity and the first nominal peak intensity comprises calculating afirst signal-to-noise ratio of the first peak intensity to the firstnominal peak intensity; and wherein pairing the first reporter gene withthe first promoter gene in response to the difference exceeding thethreshold difference comprises pairing the first reporter gene with thefirst promoter gene in response to the first signal-to-noise exceeding athreshold signal-to-noise ratio.
 17. The method of claim 15, furthercomprising, genetically modifying the population of sensor plants toinclude the first promoter-reporter pair to configure the population ofsensor plant to signal presence of the first stressor, the firstpromoter-reporter pair comprising: the first promoter gene configured toexpress responsive to presence of the target stressor; and the firstreporter gene linked to the first promoter gene and configured toexpress a fluorescence signal, at the first wavelength, responsive toexpression of the first promoter gene, the fluorescence signalrepresenting presence of the target stressor.
 18. The method of claim15, further comprising, in response to the difference falling below thethreshold difference: rejecting the first reporter; accessing a secondfluorescent light spectrum depicting fluorescence of a second reportergene in the set of reporter genes; accessing a second peak intensity, ata second wavelength, in the second fluorescent light spectrum; accessinga second nominal peak intensity, at the second wavelength, in thenominal upwelling light spectrum; characterizing a second differencebetween the second peak intensity and the second nominal peak intensity;and in response to the second difference exceeding the thresholddifference, pairing the second reporter gene with the first promotergene to form a second promoter-reporter pair configured to transientlyexpress fluorescence signals, at the second wavelength, responsive topresence of the target stressor at sensor plants of the sensor planttype.
 19. The method of claim 15, further comprising: accessing a secondfluorescent light spectrum depicting fluorescence of a second reportergene in the set of reporter genes; accessing a second peak intensity, ata second wavelength, in the second fluorescent light spectrum;calculating a distance between the first wavelength and the secondwavelength; and in response to the distance exceeding a thresholddistance: accessing a second nominal peak intensity, at the secondwavelength, in the nominal upwelling light spectrum; characterizing asecond difference between the second peak intensity and the secondnominal peak intensity; and in response to the second differenceexceeding the threshold difference: accessing a second target stressor,in the set of stressors, defined for sensor plants of the sensor planttype; and pairing the second reporter gene with a second promoter gene,in the set of promoter genes, to form a second promoter-reporter pairconfigured to transiently express fluorescence signals, at the secondwavelength, responsive to presence of the second target stressor atsensor plants of the sensor plant type.
 20. The method of claim 19:wherein accessing the first nominal peak intensity at the firstwavelength comprises accessing the first nominal peak intensity at thefirst wavelength corresponding to a first spectral absorption line, in aset of spectral absorption lines, depicted in the nominal upwellinglight spectrum; and wherein accessing the second nominal peak intensityat the second wavelength comprises accessing the second nominal peakintensity at the second wavelength corresponding to a second spectralabsorption line, in the set of spectral absorption lines, depicted inthe nominal upwelling light spectrum.